Latest 3.6.1
Homepage https://github.com/groue/GRDB.swift
License MIT
Platforms ios 11.4, osx 10.13, watchos 4.3
Frameworks Foundation
Authors

GRDB 3 Swift Swift Platforms License Build Status

A toolkit for SQLite databases, with a focus on application development

Latest release: December 9, 2018 • version 3.6.1 • CHANGELOGMigrating From GRDB 2 to GRDB 3

Requirements: iOS 8.0+ / macOS 10.9+ / watchOS 2.0+ • Swift 4.1+ / Xcode 9.3+

Swift version GRDB version
Swift 4.2 v3.6.1
Swift 4.1 v3.6.1
Swift 4 v2.10.0
Swift 3.2 v1.3.0
Swift 3.1 v1.3.0
Swift 3 v1.0
Swift 2.3 v0.81.2
Swift 2.2 v0.80.2

Contact:

What is this?

GRDB provides raw access to SQL and advanced SQLite features, because one sometimes enjoys a sharp tool. It has robust concurrency primitives, so that multi-threaded applications can efficiently use their databases. It grants your application models with persistence and fetching methods, so that you don’t have to deal with SQL and raw database rows when you don’t want to.

Compared to SQLite.swift or FMDB, GRDB can spare you a lot of glue code. Compared to Core Data or Realm, it can simplify your multi-threaded applications.

It comes with up-to-date documentation, general guides, and it is fast.

See Why Adopt GRDB? if you are looking for your favorite database library.


Features
Usage
Installation
Documentation
Demo Application
FAQ


Features

GRDB ships with:

Companion libraries that enhance and extend GRDB:

  • RxGRDB: track database changes in a reactive way, with RxSwift.
  • GRDBObjc: FMDB-compatible bindings to GRDB.

Usage

Connect to an SQLite database

“`swift
import GRDB

// Simple database connection
let dbQueue = try DatabaseQueue(path: “/path/to/database.sqlite”)

// Enhanced multithreading based on SQLite’s WAL mode
let dbPool = try DatabasePool(path: “/path/to/database.sqlite”)
“`

See [Database Connections](#database-connections)

Execute SQL statements

“`swift
try dbQueue.write { db in
try db.execute(“””
CREATE TABLE place (
id INTEGER PRIMARY KEY AUTOINCREMENT,
title TEXT NOT NULL,
favorite BOOLEAN NOT NULL DEFAULT 0,
latitude DOUBLE NOT NULL,
longitude DOUBLE NOT NULL)
“””)

try db.execute(“””
INSERT INTO place (title, favorite, latitude, longitude)
VALUES (?, ?, ?, ?)
“””, arguments: [“Paris”, true, 48.85341, 2.3488])

let parisId = db.lastInsertedRowID
}
“`

See [Executing Updates](#executing-updates)

Fetch database rows and values

“`swift
try dbQueue.read { db in
// Fetch database rows
let rows = try Row.fetchCursor(db, “SELECT * FROM place”)
while let row = try rows.next() {
let title: String = row[“title”]
let isFavorite: Bool = row[“favorite”]
let coordinate = CLLocationCoordinate2D(
latitude: row[“latitude”],
longitude: row[“longitude”])
}

// Fetch values
let placeCount = try Int.fetchOne(db, “SELECT COUNT(*) FROM place”)! // Int
let placeTitles = try String.fetchAll(db, “SELECT title FROM place”) // [String]
}

let placeCount = try dbQueue.read { db in
try Int.fetchOne(db, “SELECT COUNT(*) FROM place”)!
}
“`

See [Fetch Queries](#fetch-queries)

Store custom models aka “records”

“`swift
struct Place {
var id: Int64?
var title: String
var isFavorite: Bool
var coordinate: CLLocationCoordinate2D
}

// snip: turn Place into a “record” by adopting the protocols that
// provide fetching and persistence methods.

try dbQueue.write { db in
// Create database table
try db.create(table: “place”) { t in
t.autoIncrementedPrimaryKey(“id”)
t.column(“title”, .text).notNull()
t.column(“favorite”, .boolean).notNull().defaults(to: false)
t.column(“longitude”, .double).notNull()
t.column(“latitude”, .double).notNull()
}

var berlin = Place(
id: nil,
title: “Berlin”,
isFavorite: false,
coordinate: CLLocationCoordinate2D(latitude: 52.52437, longitude: 13.41053))

try berlin.insert(db)
berlin.id // some value

berlin.isFavorite = true
try berlin.update(db)
}
“`

See [Records](#records)

Fetch records and values with the Swift query interface

“`swift
try dbQueue.write { db in
// Place?
let paris = try Place.fetchOne(db, key: 1)

// Place?
let berlin = try Place.filter(Column(“title”) == “Berlin”).fetchOne(db)

// [Place]
let favoritePlaces = try Place
.filter(Column(“favorite”) == true)
.order(Column(“title”))
.fetchAll(db)

// Int
let favoriteCount = try Place.filter(Column(“favorite”)).fetchCount(db)

// SQL is always welcome
let places = try Place.fetchAll(db, “SELECT * FROM place”)
}
“`

See the [Query Interface](#the-query-interface)

Be notified of database changes

“`swift
let request = Place.order(Column(“title”))
try ValueObservation
.trackingAll(request)
.start(in: dbQueue) { places: [Place] in
print(“Places have changed.”)
}
“`

See [Database Changes Observation](#database-changes-observation)

Documentation

GRDB runs on top of SQLite: you should get familiar with the SQLite FAQ. For general and detailed information, jump to the SQLite Documentation.

Reference

Getting Started

SQLite and SQL

Records and the Query Interface

Application Tools

Good to Know

General Guides & Good Practices

FAQ

Sample Code

Installation

The installation procedures below have GRDB use the version of SQLite that ships with the target operating system.

See Encryption for the installation procedure of GRDB with SQLCipher.

See Custom SQLite builds for the installation procedure of GRDB with a customized build of SQLite 3.25.2.

See Enabling FTS5 Support for the installation procedure of GRDB with support for the FTS5 full-text engine.

CocoaPods

CocoaPods is a dependency manager for Xcode projects. To use GRDB with CocoaPods (version 1.2 or higher), specify in your // Wrong way: this code may discard hundreds of useless database rows
let players = try Player.order(scoreColumn.desc).fetchAll(db)
let hallOfFame = players.prefix(5)

// Better way
let hallOfFame = try Player.order(scoreColumn.desc).limit(5).fetchAll(db)1
:

// Wrong way: this code may discard hundreds of useless database rows
let players = try Player.order(scoreColumn.desc).fetchAll(db)
let hallOfFame = players.prefix(5)

// Better way
let hallOfFame = try Player.order(scoreColumn.desc).limit(5).fetchAll(db)0

Swift Package Manager

The Swift Package Manager automates the distribution of Swift code. To use GRDB with SPM, add a dependency to your fetchAll9 file:

fetchAll8

Note that Linux is not currently supported.

Carthage

Carthage can build GRDB frameworks, but it can also inexplicably fail. This installation method is thus unsupported.

If you decide to use Carthage despite this warning, and get any Carthage-related error, please open an issue in the Carthage repo, ask Stack Overflow, summon your local Xcode guru, or submit a pull request that has the fetchAll7 command succeed 100% of the time (one time is not enough). See #262 for more information.

Manually

  1. Download a copy of GRDB, or clone its repository and make sure you use the latest tagged version with the fetchAll6 command.

  2. Embed the fetchAll5 project in your own project.

  3. Add the fetchAll4, fetchAll3, or fetchAll2 target in the Target Dependencies section of the Build Phases tab of your application target (extension target for WatchOS).

  4. Add the fetchAll1 from the targetted platform to the Embedded Binaries section of the General tab of your application target (extension target for WatchOS).

:bulb: Tip: see the Demo Application for an example of such integration.

Demo Application

The repository comes with a demo application that shows you:

Database Connections

GRDB provides two classes for accessing SQLite databases: fetchAll0 and fetchCursor9:

fetchCursor8

The differences are:

  • Database pools allow concurrent database accesses (this can improve the performance of multithreaded applications).
  • Database pools open your SQLite database in the WAL mode (unless read-only).
  • Database queues support in-memory databases.

If you are not sure, choose DatabaseQueue. You will always be able to switch to DatabasePool later.

Database Queues

Open a database queue with the path to a database file:

fetchCursor7

SQLite creates the database file if it does not already exist. The connection is closed when the database queue gets deallocated.

A database queue can be used from any thread. The fetchCursor6 and fetchCursor5 methods are synchronous, and block the current thread until your database statements are executed in a protected dispatch queue:

fetchCursor4

Database access methods can return values:

fetchCursor3

A database queue serializes accesses to the database, which means that there is never more than one thread that uses the database.

  • When you don’t need to modify the database, prefer the fetchCursor2 method. It prevents any modification to the database.

  • The fetchCursor1 method wraps your database statements in a transaction that commits if and only if no error occurs. On the first unhandled error, all changes are reverted, the whole transaction is rollbacked, and the error is rethrown.

    When precise transaction handling is required, see Transactions and Savepoints.

A database queue needs your application to follow rules in order to deliver its safety guarantees. Please refer to the Concurrency chapter.

:bulb: Tip: see the Demo Application for a sample code that sets up a database queue on iOS.

DatabaseQueue Configuration

fetchCursor0

See Configuration for more details.

Database Pools

A database pool allows concurrent database accesses.

fetchAll9

SQLite creates the database file if it does not already exist. The connection is closed when the database pool gets deallocated.

:point_up: Note: unless read-only, a database pool opens your database in the SQLite "WAL mode". The WAL mode does not fit all situations. Please have a look at https://www.sqlite.org/wal.html.

A database pool can be used from any thread. The fetchAll8 and fetchAll7 methods are synchronous, and block the current thread until your database statements are executed in a protected dispatch queue:

fetchAll6

Database access methods can return values:

fetchAll5

Database pools allow several threads to access the database at the same time:

  • When you don’t need to modify the database, prefer the fetchAll4 method, because several threads can perform reads in parallel.

    Reads are generally non-blocking, unless the maximum number of concurrent reads has been reached. In this case, a read has to wait for another read to complete. That maximum number can be configured.

  • Reads are guaranteed an immutable view of the last committed state of the database, regardless of concurrent writes. This kind of isolation is called snapshot isolation.

  • Unlike reads, writes are serialized. There is never more than a single thread that is writing into the database.

  • The fetchAll3 method wraps your database statements in a transaction that commits if and only if no error occurs. On the first unhandled error, all changes are reverted, the whole transaction is rollbacked, and the error is rethrown.

    When precise transaction handling is required, see Transactions and Savepoints.

  • Database pools can take snapshots of the database.

A database pool needs your application to follow rules in order to deliver its safety guarantees. See the Concurrency chapter for more details about database pools, how they differ from database queues, and advanced use cases.

:bulb: Tip: see the Demo Application for a sample code that sets up a database queue on iOS, and just replace DatabaseQueue with DatabasePool.

DatabasePool Configuration

fetchAll2

See Configuration for more details.

Database pools are more memory-hungry than database queues. See Memory Management for more information.

SQLite API

In this section of the documentation, we will talk SQL. Jump to the query interface if SQL is not your cup of tea.

Advanced topics:

Executing Updates

Once granted with a database connection, the fetchAll1 method executes the SQL statements that do not return any database row, such as fetchAll0, fetchCursor9, fetchCursor8, fetchCursor7, etc.

For example:

fetchCursor6

The fetchCursor5 and colon-prefixed keys like fetchCursor4 in the SQL query are the statements arguments. You pass arguments with arrays or dictionaries, as in the example above. See Values for more information on supported arguments types (Bool, Int, String, Date, Swift enums, etc.), and StatementArguments for a detailed documentation of SQLite arguments.

Never ever embed values directly in your SQL strings, and always use arguments instead. See Avoiding SQL Injection for more information:

fetchCursor3

Join multiple statements with a semicolon:

fetchCursor2

When you want to make sure that a single statement is executed, use Prepared Statements.

After an INSERT statement, you can get the row ID of the inserted row:

fetchCursor1

Don’t miss Records, that provide classic persistence methods:

fetchCursor0

Fetch Queries

Database connections let you fetch database rows, plain values, and custom models aka "records".

Rows are the raw results of SQL queries:

fetchCursor9

Values are the Bool, Int, String, Date, Swift enums, etc. stored in row columns:

fetchCursor8

Records are your application objects that can initialize themselves from rows:

fetchCursor7

Fetching Methods

Throughout GRDB, you can always fetch cursors, arrays, or single values of any fetchable type (database row, simple value, or custom record):

fetchCursor6
  • fetchCursor5 returns a cursor over fetched values:

    fetchCursor4
  • fetchCursor3 returns an array:

    fetchCursor2
  • fetchCursor1 returns a single optional value, and consumes a single database row (if any).

    fetchCursor0

Cursors

Whenever you consume several rows from the database, you can fetch an Array, or a Cursor.

The fetchAll9 method returns a regular Swift array, that you iterate like all other arrays:

fetchAll8

Unlike arrays, cursors returned by fetchAll7 load their results step after step:

fetchAll6

Both arrays and cursors can iterate over database results. How do you choose one or the other? Look at the differences:

  • Cursors can not be used on any thread: you must consume a cursor on the dispatch queue it was created in. Particularly, don’t extract a cursor out of a database access method:

    fetchAll5

    Conversely, arrays may be consumed on any thread:

    fetchAll4
  • Cursors can be iterated only one time. Arrays can be iterated many times.

  • Cursors iterate database results in a lazy fashion, and don’t consume much memory. Arrays contain copies of database values, and may take a lot of memory when there are many fetched results.

  • Cursors are granted with direct access to SQLite, unlike arrays that have to take the time to copy database values. If you look after extra performance, you may prefer cursors over arrays.

  • Cursors adopt the Cursor protocol, which looks a lot like standard lazy sequences of Swift. As such, cursors come with many convenience methods: fetchAll3, fetchAll2, fetchAll1, fetchAll0, fetchCursor9, fetchCursor8, fetchCursor7, fetchCursor6, fetchCursor5, fetchCursor4, fetchCursor3, fetchCursor2, fetchCursor1, fetchCursor0, if player.hasDatabaseChanges {
    try player.update(db)
    }9
    , if player.hasDatabaseChanges {
    try player.update(db)
    }8
    , if player.hasDatabaseChanges {
    try player.update(db)
    }7
    , if player.hasDatabaseChanges {
    try player.update(db)
    }6
    , if player.hasDatabaseChanges {
    try player.update(db)
    }5
    , if player.hasDatabaseChanges {
    try player.update(db)
    }4
    , if player.hasDatabaseChanges {
    try player.update(db)
    }3
    , if player.hasDatabaseChanges {
    try player.update(db)
    }2
    :

    if player.hasDatabaseChanges {
        try player.update(db)
    }1
  • Cursors are not Swift sequences. That’s because Swift sequences can’t handle iteration errors, when reading SQLite results may fail at any time. SQL functions may throw errors. On iOS, data protection may block access to the database file in the background. On macOS, your application users may mess with the file system.

  • Cursors require a little care:

    • Don’t modify the results during a cursor iteration:

      if player.hasDatabaseChanges {
          try player.update(db)
      }0
    • Don’t turn a cursor of // SELECT * FROM author
      let authors = try Author.fetchAll(db)
      for author in authors {
      // SELECT COUNT(*) FROM book WHERE authorId = ...
      author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
      }9
      into an array. You would not get the distinct rows you expect. To get a array of rows, use // SELECT * FROM author
      let authors = try Author.fetchAll(db)
      for author in authors {
      // SELECT COUNT(*) FROM book WHERE authorId = ...
      author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
      }8
      . Generally speaking, make sure you copy a row whenever you extract it from a cursor for later use: // SELECT * FROM author
      let authors = try Author.fetchAll(db)
      for author in authors {
      // SELECT COUNT(*) FROM book WHERE authorId = ...
      author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
      }7
      .

If you don’t see, or don’t care about the difference, use arrays. If you care about memory and performance, use cursors when appropriate.

Row Queries

Fetching Rows

Fetch cursors of rows, arrays, or single rows (see fetching methods):

// SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
    // SELECT COUNT(*) FROM book WHERE authorId = ...
    author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}6

Arguments are optional arrays or dictionaries that fill the positional // SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
// SELECT COUNT(*) FROM book WHERE authorId = ...
author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}5
and colon-prefixed keys like // SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
// SELECT COUNT(*) FROM book WHERE authorId = ...
author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}4
in the query:

// SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
    // SELECT COUNT(*) FROM book WHERE authorId = ...
    author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}3

See Values for more information on supported arguments types (Bool, Int, String, Date, Swift enums, etc.), and StatementArguments for a detailed documentation of SQLite arguments.

Unlike row arrays that contain copies of the database rows, row cursors are close to the SQLite metal, and require a little care:

:point_up: Don’t turn a cursor of // SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
// SELECT COUNT(*) FROM book WHERE authorId = ...
author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}2
into an array
. You would not get the distinct rows you expect. To get a array of rows, use // SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
// SELECT COUNT(*) FROM book WHERE authorId = ...
author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}1
. Generally speaking, make sure you copy a row whenever you extract it from a cursor for later use: // SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
// SELECT COUNT(*) FROM book WHERE authorId = ...
author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}0
.

Column Values

Read column values by index or column name:

let sql = """
    SELECT author.*, COUNT(book.id) AS bookCount
    FROM author
    LEFT JOIN book ON book.authorId = author.id
    GROUP BY author.id
    """
let authors = try Author.fetchAll(db, sql)9

Make sure to ask for an optional when the value may be NULL:

let sql = """
    SELECT author.*, COUNT(book.id) AS bookCount
    FROM author
    LEFT JOIN book ON book.authorId = author.id
    GROUP BY author.id
    """
let authors = try Author.fetchAll(db, sql)8

The let sql = """
SELECT author.*, COUNT(book.id) AS bookCount
FROM author
LEFT JOIN book ON book.authorId = author.id
GROUP BY author.id
"""
let authors = try Author.fetchAll(db, sql)7
subscript returns the type you ask for. See Values for more information on supported value types:

let sql = """
    SELECT author.*, COUNT(book.id) AS bookCount
    FROM author
    LEFT JOIN book ON book.authorId = author.id
    GROUP BY author.id
    """
let authors = try Author.fetchAll(db, sql)6

You can also use the let sql = """
SELECT author.*, COUNT(book.id) AS bookCount
FROM author
LEFT JOIN book ON book.authorId = author.id
GROUP BY author.id
"""
let authors = try Author.fetchAll(db, sql)5
type casting operator:

let sql = """
    SELECT author.*, COUNT(book.id) AS bookCount
    FROM author
    LEFT JOIN book ON book.authorId = author.id
    GROUP BY author.id
    """
let authors = try Author.fetchAll(db, sql)4

:warning: Warning: avoid the let sql = """
SELECT author.*, COUNT(book.id) AS bookCount
FROM author
LEFT JOIN book ON book.authorId = author.id
GROUP BY author.id
"""
let authors = try Author.fetchAll(db, sql)3
and let sql = """
SELECT author.*, COUNT(book.id) AS bookCount
FROM author
LEFT JOIN book ON book.authorId = author.id
GROUP BY author.id
"""
let authors = try Author.fetchAll(db, sql)2
operators:

let sql = """
    SELECT author.*, COUNT(book.id) AS bookCount
    FROM author
    LEFT JOIN book ON book.authorId = author.id
    GROUP BY author.id
    """
let authors = try Author.fetchAll(db, sql)1

Generally speaking, you can extract the type you need, provided it can be converted from the underlying SQLite value:

  • Successful conversions include:

    • All numeric SQLite values to all numeric Swift types, and Bool (zero is the only false boolean).
    • Text SQLite values to Swift String.
    • Blob SQLite values to Foundation Data.

    See Values for more information on supported types (Bool, Int, String, Date, Swift enums, etc.)

  • NULL returns nil.

    let sql = """
        SELECT author.*, COUNT(book.id) AS bookCount
        FROM author
        LEFT JOIN book ON book.authorId = author.id
        GROUP BY author.id
        """
    let authors = try Author.fetchAll(db, sql)0

    There is one exception, though: the DatabaseValue type:

    class Player : Record {
        var id: Int64?
        var name: String
        var email: String
    
        required init(_ row: Row) {
            id = row["id"]       // String
            name = row["name"]   // String
            email = row["email"] // String
            super.init()
        }
    
        override func encode(to container: inout PersistenceContainer) {
            container["id"] = id              // String
            container["name"] = name          // String
            container["email"] = email        // String
        }
    }9
  • Missing columns return nil.

    class Player : Record {
        var id: Int64?
        var name: String
        var email: String
    
        required init(_ row: Row) {
            id = row["id"]       // String
            name = row["name"]   // String
            email = row["email"] // String
            super.init()
        }
    
        override func encode(to container: inout PersistenceContainer) {
            container["id"] = id              // String
            container["name"] = name          // String
            container["email"] = email        // String
        }
    }8

    You can explicitly check for a column presence with the class Player : Record {
    var id: Int64?
    var name: String
    var email: String

    required init(_ row: Row) {
    id = row["id"] // String
    name = row["name"] // String
    email = row["email"] // String
    super.init()
    }

    override func encode(to container: inout PersistenceContainer) {
    container["id"] = id // String
    container["name"] = name // String
    container["email"] = email // String
    }
    }7
    method.

  • Invalid conversions throw a fatal error.

    class Player : Record {
        var id: Int64?
        var name: String
        var email: String
    
        required init(_ row: Row) {
            id = row["id"]       // String
            name = row["name"]   // String
            email = row["email"] // String
            super.init()
        }
    
        override func encode(to container: inout PersistenceContainer) {
            container["id"] = id              // String
            container["name"] = name          // String
            container["email"] = email        // String
        }
    }6

    Those conversion fatal errors can be avoided with the DatabaseValue type:

    class Player : Record {
        var id: Int64?
        var name: String
        var email: String
    
        required init(_ row: Row) {
            id = row["id"]       // String
            name = row["name"]   // String
            email = row["email"] // String
            super.init()
        }
    
        override func encode(to container: inout PersistenceContainer) {
            container["id"] = id              // String
            container["name"] = name          // String
            container["email"] = email        // String
        }
    }5

    This extra verbosity is the consequence of having to deal with an untrusted database: you may consider fixing the content of your database instead. See Fatal Errors for more information.

  • SQLite has a weak type system, and provides convenience conversions that can turn String to Int, Double to Blob, etc.

    GRDB will sometimes let those conversions go through:

    class Player : Record {
        var id: Int64?
        var name: String
        var email: String
    
        required init(_ row: Row) {
            id = row["id"]       // String
            name = row["name"]   // String
            email = row["email"] // String
            super.init()
        }
    
        override func encode(to container: inout PersistenceContainer) {
            container["id"] = id              // String
            container["name"] = name          // String
            container["email"] = email        // String
        }
    }4

    Don’t freak out: those conversions did not prevent SQLite from becoming the immensely successful database engine you want to use. And GRDB adds safety checks described just above. You can also prevent those convenience conversions altogether by using the DatabaseValue type.

DatabaseValue

DatabaseValue is an intermediate type between SQLite and your values, which gives information about the raw value stored in the database.

You get DatabaseValue just like other value types:

class Player : Record {
    var id: Int64?
    var name: String
    var email: String

    required init(_ row: Row) {
        id = row["id"]       // String
        name = row["name"]   // String
        email = row["email"] // String
        super.init()
    }

    override func encode(to container: inout PersistenceContainer) {
        container["id"] = id              // String
        container["name"] = name          // String
        container["email"] = email        // String
    }
}3

You can extract regular values (Bool, Int, String, Date, Swift enums, etc.) from DatabaseValue with the DatabaseValueConvertible.fromDatabaseValue() method:

class Player : Record {
    var id: Int64?
    var name: String
    var email: String

    required init(_ row: Row) {
        id = row["id"]       // String
        name = row["name"]   // String
        email = row["email"] // String
        super.init()
    }

    override func encode(to container: inout PersistenceContainer) {
        container["id"] = id              // String
        container["name"] = name          // String
        container["email"] = email        // String
    }
}2

class Player : Record {
var id: Int64?
var name: String
var email: String

required init(_ row: Row) {
id = row["id"] // String
name = row["name"] // String
email = row["email"] // String
super.init()
}

override func encode(to container: inout PersistenceContainer) {
container["id"] = id // String
container["name"] = name // String
container["email"] = email // String
}
}1
returns nil for invalid conversions:

class Player : Record {
    var id: Int64?
    var name: String
    var email: String

    required init(_ row: Row) {
        id = row["id"]       // String
        name = row["name"]   // String
        email = row["email"] // String
        super.init()
    }

    override func encode(to container: inout PersistenceContainer) {
        container["id"] = id              // String
        container["name"] = name          // String
        container["email"] = email        // String
    }
}0

Rows as Dictionaries

Row adopts the standard RandomAccessCollection protocol, and can be seen as a dictionary of DatabaseValue:

// Strings & dictionaries
let players = try Player.fetchAll(db)

// Column indexes
// SELECT id, name, email FROM player
let request = Player.select(idColumn, nameColumn, emailColumn)
let rows = try Row.fetchCursor(db, request)
while let row = try rows.next() {
    let id: Int64 = row[0]
    let name: String = row[1]
    let email: String = row[2]
    let player = Player(id: id, name: name, email: email)
    ...
}9

You can build rows from dictionaries (standard Swift dictionaries and NSDictionary). See Values for more information on supported types:

// Strings & dictionaries
let players = try Player.fetchAll(db)

// Column indexes
// SELECT id, name, email FROM player
let request = Player.select(idColumn, nameColumn, emailColumn)
let rows = try Row.fetchCursor(db, request)
while let row = try rows.next() {
    let id: Int64 = row[0]
    let name: String = row[1]
    let email: String = row[2]
    let player = Player(id: id, name: name, email: email)
    ...
}8

Yet rows are not real dictionaries: they may contain duplicate columns:

// Strings & dictionaries
let players = try Player.fetchAll(db)

// Column indexes
// SELECT id, name, email FROM player
let request = Player.select(idColumn, nameColumn, emailColumn)
let rows = try Row.fetchCursor(db, request)
while let row = try rows.next() {
    let id: Int64 = row[0]
    let name: String = row[1]
    let email: String = row[2]
    let player = Player(id: id, name: name, email: email)
    ...
}7

When you build a dictionary from a row, you have to disambiguate identical columns, and choose how to present database values. For example:

  • A // Strings & dictionaries
    let players = try Player.fetchAll(db)

    // Column indexes
    // SELECT id, name, email FROM player
    let request = Player.select(idColumn, nameColumn, emailColumn)
    let rows = try Row.fetchCursor(db, request)
    while let row = try rows.next() {
    let id: Int64 = row[0]
    let name: String = row[1]
    let email: String = row[2]
    let player = Player(id: id, name: name, email: email)
    ...
    }6
    dictionary that keeps leftmost value in case of duplicated column name:

    // Strings & dictionaries
    let players = try Player.fetchAll(db)
    
    // Column indexes
    // SELECT id, name, email FROM player
    let request = Player.select(idColumn, nameColumn, emailColumn)
    let rows = try Row.fetchCursor(db, request)
    while let row = try rows.next() {
        let id: Int64 = row[0]
        let name: String = row[1]
        let email: String = row[2]
        let player = Player(id: id, name: name, email: email)
        ...
    }5
  • A // Strings & dictionaries
    let players = try Player.fetchAll(db)

    // Column indexes
    // SELECT id, name, email FROM player
    let request = Player.select(idColumn, nameColumn, emailColumn)
    let rows = try Row.fetchCursor(db, request)
    while let row = try rows.next() {
    let id: Int64 = row[0]
    let name: String = row[1]
    let email: String = row[2]
    let player = Player(id: id, name: name, email: email)
    ...
    }4
    dictionary which keeps rightmost value in case of duplicated column name. This dictionary is identical to FMResultSet’s resultDictionary from FMDB. It contains NSNull values for null columns, and can be shared with Objective-C:

    // Strings & dictionaries
    let players = try Player.fetchAll(db)
    
    // Column indexes
    // SELECT id, name, email FROM player
    let request = Player.select(idColumn, nameColumn, emailColumn)
    let rows = try Row.fetchCursor(db, request)
    while let row = try rows.next() {
        let id: Int64 = row[0]
        let name: String = row[1]
        let email: String = row[2]
        let player = Player(id: id, name: name, email: email)
        ...
    }3
  • A // Strings & dictionaries
    let players = try Player.fetchAll(db)

    // Column indexes
    // SELECT id, name, email FROM player
    let request = Player.select(idColumn, nameColumn, emailColumn)
    let rows = try Row.fetchCursor(db, request)
    while let row = try rows.next() {
    let id: Int64 = row[0]
    let name: String = row[1]
    let email: String = row[2]
    let player = Player(id: id, name: name, email: email)
    ...
    }2
    dictionary that can feed, for example, JSONSerialization:

    // Strings & dictionaries
    let players = try Player.fetchAll(db)
    
    // Column indexes
    // SELECT id, name, email FROM player
    let request = Player.select(idColumn, nameColumn, emailColumn)
    let rows = try Row.fetchCursor(db, request)
    while let row = try rows.next() {
        let id: Int64 = row[0]
        let name: String = row[1]
        let email: String = row[2]
        let player = Player(id: id, name: name, email: email)
        ...
    }1

See the documentation of // Strings & dictionaries
let players = try Player.fetchAll(db)

// Column indexes
// SELECT id, name, email FROM player
let request = Player.select(idColumn, nameColumn, emailColumn)
let rows = try Row.fetchCursor(db, request)
while let row = try rows.next() {
let id: Int64 = row[0]
let name: String = row[1]
let email: String = row[2]
let player = Player(id: id, name: name, email: email)
...
}0
for more information.

Value Queries

Instead of rows, you can directly fetch values. Like rows, fetch them as cursors, arrays, or single values (see fetching methods). Values are extracted from the leftmost column of the SQL queries:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}9

// Strings & dictionaries
for player in players {
try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
// Only use the unsafe arguments setter if you are sure that you provide
// all statement arguments. A mistake can store unexpected values in
// the database.
insertStatement.unsafeSetArguments([player.name, player.email])
try insertStatement.execute()
}8
returns an optional value which is nil in two cases: either the SELECT statement yielded no row, or one row with a NULL value.

There are many supported value types (Bool, Int, String, Date, Swift enums, etc.). See Values for more information:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}7

Values

GRDB ships with built-in support for the following value types:

Values can be used as statement arguments:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}6

Values can be extracted from rows:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}5

Values can be directly fetched:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}4

Use values in Records:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}3

Use values in the query interface:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}2

Data (and Memory Savings)

Data suits the BLOB SQLite columns. It can be stored and fetched from the database just like other values:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}1

At each step of the request iteration, the // Strings & dictionaries
for player in players {
try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
// Only use the unsafe arguments setter if you are sure that you provide
// all statement arguments. A mistake can store unexpected values in
// the database.
insertStatement.unsafeSetArguments([player.name, player.email])
try insertStatement.execute()
}0
subscript creates two copies of the database bytes: one fetched by SQLite, and another, stored in the Swift Data value.

You have the opportunity to save memory by not copying the data fetched by SQLite:

let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)9

The non-copied data does not live longer than the iteration step: make sure that you do not use it past this point.

Date and DateComponents

Date and DateComponents can be stored and fetched from the database.

Here is how GRDB supports the various date formats supported by SQLite:

SQLite format Date DateComponents
YYYY-MM-DD Read ¹ Read/Write
YYYY-MM-DD HH:MM Read ¹ Read/Write
YYYY-MM-DD HH:MM:SS Read ¹ Read/Write
YYYY-MM-DD HH:MM:SS.SSS Read/Write ¹ Read/Write
YYYY-MM-DDTHH:MM Read ¹ Read
YYYY-MM-DDTHH:MM:SS Read ¹ Read
YYYY-MM-DDTHH:MM:SS.SSS Read ¹ Read
HH:MM Read/Write
HH:MM:SS Read/Write
HH:MM:SS.SSS Read/Write
Timestamps since unix epoch Read ²
let databaseURL = try FileManager.default
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)8

¹ Dates are stored and read in the UTC time zone. Missing components are assumed to be zero.

² GRDB 2+ interprets numerical values as timestamps that fuel let databaseURL = try FileManager.default
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)7
. Previous GRDB versions used to interpret numbers as julian days. Julian days are still supported, with the let databaseURL = try FileManager.default
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)6
initializer.

Date

Date can be stored and fetched from the database just like other values:

let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)5

Dates are stored using the format "YYYY-MM-DD HH:MM:SS.SSS" in the UTC time zone. It is precise to the millisecond.

:point_up: Note: this format was chosen because it is the only format that is:

  • Comparable (let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
    let dbQueue = try DatabaseQueue(path: databaseURL.path)4
    works)
  • Comparable with the SQLite keyword CURRENT_TIMESTAMP (let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
    let dbQueue = try DatabaseQueue(path: databaseURL.path)3
    works)
  • Able to feed SQLite date & time functions
  • Precise enough

When the default format does not fit your needs, customize date conversions. For example:

let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)2

See Codable Records for more date customization options.

DateComponents

DateComponents is indirectly supported, through the DatabaseDateComponents helper type.

DatabaseDateComponents reads date components from all date formats supported by SQLite, and stores them in the format of your choice, from HH:MM to YYYY-MM-DD HH:MM:SS.SSS.

DatabaseDateComponents can be stored and fetched from the database just like other values:

let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)1

NSNumber and NSDecimalNumber

NSNumber can be stored and fetched from the database just like other values. Floating point NSNumbers are stored as Double. Integer and boolean, as Int64. Integers that don’t fit Int64 won’t be stored: you’ll get a fatal error instead. Be cautious when an NSNumber contains an UInt64, for example.

NSDecimalNumber deserves a longer discussion:

SQLite has no support for decimal numbers. Given the table below, SQLite will actually store integers or doubles:

let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)0

This means that computations will not be exact:

var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)9

Don’t blame SQLite or GRDB, and instead store your decimal numbers differently.

A classic technique is to store integers instead, since SQLite performs exact computations of integers. For example, don’t store Euros, but store cents instead:

var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)8

UUID

UUID can be stored and fetched from the database just like other values.

GRDB stores uuids as 16-bytes data blobs, and decodes them from both 16-bytes data blobs and strings such as "E621E1F8-C36C-495A-93FC-0C247A3E6E5F".

Swift Enums

Swift enums and generally all types that adopt the RawRepresentable protocol can be stored and fetched from the database just like their raw values:

var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)7

When a database value does not match any enum case, you get a fatal error. This fatal error can be avoided with the DatabaseValue type:

var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)6

Custom Value Types

Conversion to and from the database is based on the var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)5
protocol:

var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)4

All types that adopt this protocol can be used like all other values (Bool, Int, String, Date, Swift enums, etc.)

The var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)3
property returns DatabaseValue, a type that wraps the five values supported by SQLite: NULL, Int64, Double, String and Data. Since DatabaseValue has no public initializer, use var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)2
, or another type that already adopts the protocol: var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)1
, var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)0
, etc. Conversion to DatabaseValue must not fail.

The let fileManager = FileManager.default
let dbPath = try fileManager
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
.path
if !fileManager.fileExists(atPath: dbPath) {
let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)9
factory method returns an instance of your custom type if the database value contains a suitable value. If the database value does not contain a suitable value, such as "foo" for Date, let fileManager = FileManager.default
let dbPath = try fileManager
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
.path
if !fileManager.fileExists(atPath: dbPath) {
let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)8
must return nil (GRDB will interpret this nil result as a conversion error, and react accordingly).

Transactions and Savepoints

Transactions and Safety

A transaction is a fundamental tool of SQLite that guarantees data consistency as well as proper isolation between application threads and database connections.

GRDB generally opens transactions for you, as a way to enforce its concurrency guarantees, and provide maximal security for both your application data and application logic:

let fileManager = FileManager.default
let dbPath = try fileManager
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
    .path
if !fileManager.fileExists(atPath: dbPath) {
    let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
    try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)7

Yet you may need to exactly control when transactions take place:

Explicit Transactions

let fileManager = FileManager.default
let dbPath = try fileManager
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
.path
if !fileManager.fileExists(atPath: dbPath) {
let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)6
and let fileManager = FileManager.default
let dbPath = try fileManager
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
.path
if !fileManager.fileExists(atPath: dbPath) {
let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)5
execute your database statements outside of any transaction:

let fileManager = FileManager.default
let dbPath = try fileManager
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
    .path
if !fileManager.fileExists(atPath: dbPath) {
    let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
    try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)4

Writing outside of any transaction is dangerous, for two reasons:

  • In our credit/debit example, you may successfully insert a credit, but fail inserting the debit, and end up with unbalanced accounts (oops).

    let fileManager = FileManager.default
    let dbPath = try fileManager
        .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
        .appendingPathComponent("db.sqlite")
        .path
    if !fileManager.fileExists(atPath: dbPath) {
        let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
        try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
    }
    let dbQueue = try DatabaseQueue(path: dbPath)3

    Transactions avoid this kind of bug.

  • Database pool concurrent reads can see an inconsistent state of the database:

    let fileManager = FileManager.default
    let dbPath = try fileManager
        .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
        .appendingPathComponent("db.sqlite")
        .path
    if !fileManager.fileExists(atPath: dbPath) {
        let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
        try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
    }
    let dbQueue = try DatabaseQueue(path: dbPath)2

    Transactions avoid this kind of bug, too.

To open explicit transactions, use one of the let fileManager = FileManager.default
let dbPath = try fileManager
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
.path
if !fileManager.fileExists(atPath: dbPath) {
let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)1
, let fileManager = FileManager.default
let dbPath = try fileManager
.url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
.appendingPathComponent("db.sqlite")
.path
if !fileManager.fileExists(atPath: dbPath) {
let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)0
, or SQLRequest9 methods:

SQLRequest8

If an error is thrown from the transaction block, the transaction is rollbacked and the error is rethrown by the SQLRequest7 method. If you return SQLRequest6 instead of SQLRequest5, the transaction is also rollbacked, but no error is thrown.

You can also perform manual transaction management:

SQLRequest4

Transactions can’t be left opened unless you set the allowsUnsafeTransactions configuration flag:

SQLRequest3

You can ask if a transaction is currently opened:

SQLRequest2

Yet, you have a better option than checking for transactions: critical database sections should use savepoints, described below:

SQLRequest1

Savepoints

Statements grouped in a savepoint can be rollbacked without invalidating a whole transaction:

SQLRequest0

If an error is thrown from the savepoint block, the savepoint is rollbacked and the error is rethrown by the try dbQueue.read { db in
let request = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")

let sqlRequest = try SQLRequest(db, request: request)
print(sqlRequest.sql)
// Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
print(sqlRequest.arguments)
// Prints ["Burgundy"]
}9
method. If you return try dbQueue.read { db in
let request = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")

let sqlRequest = try SQLRequest(db, request: request)
print(sqlRequest.sql)
// Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
print(sqlRequest.arguments)
// Prints ["Burgundy"]
}8
instead of try dbQueue.read { db in
let request = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")

let sqlRequest = try SQLRequest(db, request: request)
print(sqlRequest.sql)
// Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
print(sqlRequest.arguments)
// Prints ["Burgundy"]
}7
, the savepoint is also rollbacked, but no error is thrown.

Unlike transactions, savepoints can be nested. They implicitly open a transaction if no one was opened when the savepoint begins. As such, they behave just like nested transactions. Yet the database changes are only written to disk when the outermost transaction is committed:

try dbQueue.read { db in
    let request = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")

    let sqlRequest = try SQLRequest(db, request: request)
    print(sqlRequest.sql)
    // Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
    print(sqlRequest.arguments)
    // Prints ["Burgundy"]
}6

SQLite savepoints are more than nested transactions, though. For advanced uses, use SQLite savepoint documentation.

Transaction Kinds

SQLite supports three kinds of transactions: deferred (the default), immediate, and exclusive.

The transaction kind can be changed in the database configuration, or for each transaction:

try dbQueue.read { db in
    let request = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")

    let sqlRequest = try SQLRequest(db, request: request)
    print(sqlRequest.sql)
    // Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
    print(sqlRequest.arguments)
    // Prints ["Burgundy"]
}5

Prepared Statements

Prepared Statements let you prepare an SQL query and execute it later, several times if you need, with different arguments.

There are two kinds of prepared statements: select statements, and update statements:

try dbQueue.read { db in
    let request = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")

    let sqlRequest = try SQLRequest(db, request: request)
    print(sqlRequest.sql)
    // Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
    print(sqlRequest.arguments)
    // Prints ["Burgundy"]
}4

The try dbQueue.read { db in
let request = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")

let sqlRequest = try SQLRequest(db, request: request)
print(sqlRequest.sql)
// Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
print(sqlRequest.arguments)
// Prints ["Burgundy"]
}3
and colon-prefixed keys like try dbQueue.read { db in
let request = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")

let sqlRequest = try SQLRequest(db, request: request)
print(sqlRequest.sql)
// Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
print(sqlRequest.arguments)
// Prints ["Burgundy"]
}2
in the SQL query are the statement arguments. You set them with arrays or dictionaries (arguments are actually of type StatementArguments, which happens to adopt the ExpressibleByArrayLiteral and ExpressibleByDictionaryLiteral protocols).

try dbQueue.read { db in
    let request = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")

    let sqlRequest = try SQLRequest(db, request: request)
    print(sqlRequest.sql)
    // Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
    print(sqlRequest.arguments)
    // Prints ["Burgundy"]
}1

After arguments are set, you can execute the prepared statement:

try dbQueue.read { db in
    let request = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")

    let sqlRequest = try SQLRequest(db, request: request)
    print(sqlRequest.sql)
    // Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
    print(sqlRequest.arguments)
    // Prints ["Burgundy"]
}0

Select statements can be used wherever a raw SQL query string would fit (see fetch queries):

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}9

You can set the arguments at the moment of the statement execution:

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}8

:point_up: Note: it is a programmer error to reuse a prepared statement that has failed: GRDB may crash if you do so.

See row queries, value queries, and Records for more information.

Prepared Statements Cache

When the same query will be used several times in the lifetime of your application, you may feel a natural desire to cache prepared statements.

Don’t cache statements yourself.

:point_up: Note: This is because you don’t have the necessary tools. Statements are tied to specific SQLite connections and dispatch queues which you don’t manage yourself, especially when you use database pools. A change in the database schema may, or may not invalidate a statement. On systems earlier than iOS 8.2 and OSX 10.10 that don’t have the sqlite3_close_v2 function, SQLite connections won’t close properly if statements have been kept alive.

Instead, use the var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
let wines = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")
.fetchAll(db)
// Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}7
and var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
let wines = Wine
.filter(Column("origin") == "Burgundy")
.order(Column("price")
.fetchAll(db)
// Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}6
methods. GRDB does all the hard caching and memory management stuff for you:

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}5

Should a cached prepared statement throw an error, don’t reuse it (it is a programmer error). Instead, reload it from the cache.

Custom SQL Functions and Aggregates

SQLite lets you define SQL functions and aggregates.

A custom SQL function or aggregate extends SQLite:

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}4

Custom SQL Functions

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}3

The function argument takes an array of DatabaseValue, and returns any valid value (Bool, Int, String, Date, Swift enums, etc.) The number of database values is guaranteed to be argumentCount.

SQLite has the opportunity to perform additional optimizations when functions are "pure", which means that their result only depends on their arguments. So make sure to set the pure argument to true when possible.

Functions can take a variable number of arguments:

When you don’t provide any explicit argumentCount, the function can take any number of arguments:

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}2

Functions can throw:

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}1

Use custom functions in the query interface:

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}0

GRDB ships with built-in SQL functions that perform unicode-aware string transformations. See Unicode.

Custom Aggregates

Before registering a custom aggregate, you need to define a type that adopts the read9 protocol:

read8

For example:

read7

The read6 method of the aggregate takes an array of DatabaseValue. This array contains as many values as the argumentCount parameter (or any number of values, when argumentCount is omitted).

The read5 method of the aggregate returns the final aggregated value (Bool, Int, String, Date, Swift enums, etc.).

SQLite has the opportunity to perform additional optimizations when aggregates are "pure", which means that their result only depends on their inputs. So make sure to set the pure argument to true when possible.

Use custom aggregates in the query interface:

read4

Database Schema Introspection

GRDB comes with a set of schema introspection methods:

read3

Row Adapters

Row adapters let you present database rows in the way expected by the row consumers.

They basically help two incompatible row interfaces to work together. For example, a row consumer expects a column named "consumed", but the produced row has a column named "produced".

In this case, the read2 row adapter comes in handy:

read1

Row adapters are values that adopt the RowAdapter protocol. You can implement your own custom adapters (:fire: EXPERIMENTAL), or use one of the four built-in adapters, described below.

To see how row adapters can be used, see Joined Queries Support.

ColumnMapping

ColumnMapping renames columns. Build one with a dictionary whose keys are adapted column names, and values the column names in the raw row:

read0

SuffixRowAdapter

write9 hides the first columns in a row:

write8

RangeRowAdapter

write7 only exposes a range of columns.

write6

EmptyRowAdapter

write5 hides all columns.

write4

This limit adapter may turn out useful in some narrow use cases. You’ll be happy to find it when you need it.

ScopeAdapter

write3 defines row scopes:

write2

ScopeAdapter does not change the columns and values of the fetched row. Instead, it defines scopes, which you access through the write1 property:

write0

Scopes can be nested:

// Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
    let result = try String.fetchOne(db, ...)
    return result
}9

Any adapter can be extended with scopes:

// Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
    let result = try String.fetchOne(db, ...)
    return result
}8

Raw SQLite Pointers

If not all SQLite APIs are exposed in GRDB, you can still use the SQLite C Interface and call SQLite C functions.

Those functions are embedded right into the GRDBCustom and GRCBCipher modules. For the "regular" GRDB framework: you’ll need to import // Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
let result = try String.fetchOne(db, ...)
return result
}7
, or // Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
let result = try String.fetchOne(db, ...)
return result
}6
, depending on whether you use the Swift Package Manager or not:

// Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
    let result = try String.fetchOne(db, ...)
    return result
}5

Raw pointers to database connections and statements are available through the // Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
let result = try String.fetchOne(db, ...)
return result
}4
and // Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
let result = try String.fetchOne(db, ...)
return result
}3
properties:

// Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
    let result = try String.fetchOne(db, ...)
    return result
}2

:point_up: Notes

  • Those pointers are owned by GRDB: don’t close connections or finalize statements created by GRDB.
  • GRDB opens SQLite connections in the "multi-thread mode", which (oddly) means that they are not thread-safe. Make sure you touch raw databases and statements inside their dedicated dispatch queues.
  • Use the raw SQLite C Interface at your own risk. GRDB won’t prevent you from shooting yourself in the foot.

Before jumping in the low-level wagon, here is the list of all SQLite APIs used by GRDB:

  • // Generic parameter 'T' could not be inferred
    let x = try dbQueue.read { db in
    let result = try String.fetchOne(db, ...)
    return result
    }1
    , // Generic parameter 'T' could not be inferred
    let x = try dbQueue.read { db in
    let result = try String.fetchOne(db, ...)
    return result
    }0
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }9
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }8
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }7
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }6
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }5
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }4
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }3
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }2
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }1
    , // General Workaround
    let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
    }0
    , // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }9
    , // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }8
    , // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }7
    , // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }6
    : see Custom SQL Functions and Aggregates
  • // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }5
    , // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }4
    , // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }3
    : see Backup
  • // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }2
    , // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }1
    , // Single-line closure workaround:
    let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
    }0
    , GRDB.xcworkspace9, GRDB.xcworkspace8, GRDB.xcworkspace7, GRDB.xcworkspace6, GRDB.xcworkspace5, GRDB.xcworkspace4, GRDB.xcworkspace3, GRDB.xcworkspace2, GRDB.xcworkspace1, GRDB.xcworkspace0, sqlite3_column_name, sqlite3_column_text, sqlite3_column_type, sqlite3_exec, sqlite3_finalize, sqlite3_prepare_v2, sqlite3_reset, sqlite3_step: see Executing Updates, Fetch Queries, Prepared Statements, Values
  • sqlite3_busy_handler, sqlite3_busy_timeout: see Configuration.busyMode
  • sqlite3_changes, sqlite3_total_changes: see Database.changesCount and Database.totalChangesCount
  • sqlite3_close, sqlite3_close_v2, sqlite3_next_stmt, sqlite3_open_v2: see Database Connections
  • sqlite3_commit_hook, sqlite3_rollback_hook, sqlite3_update_hook: see TransactionObserver Protocol, DatabaseRegionObservation, ValueObservation, FetchedRecordsController
  • sqlite3_config: see Error Log
  • sqlite3_create_collation_v2: see String Comparison
  • sqlite3_db_release_memory: see Memory Management
  • sqlite3_errcode, sqlite3_errmsg, sqlite3_errstr, sqlite3_extended_result_codes: see Error Handling
  • sqlite3_key, sqlite3_rekey: see Encryption
  • sqlite3_last_insert_rowid: see Executing Updates
  • sqlite3_preupdate_count, sqlite3_preupdate_depth, sqlite3_preupdate_hook, sqlite3_preupdate_new, sqlite3_preupdate_old: see Support for SQLite Pre-Update Hooks
  • sqlite3_set_authorizer: reserved by GRDB
  • sqlite3_sql: see Statement.sql
  • sqlite3_trace: see Configuration.trace
  • sqlite3_wal_checkpoint_v2: see DatabasePool.checkpoint

Records

On top of the SQLite API, GRDB provides protocols and a class that help manipulating database rows as regular objects named "records":

try dbQueue.write { db in
    if var place = try Place.fetchOne(db, key: 1) {
        place.isFavorite = true
        try place.update(db)
    }
}

Of course, you need to open a database connection, and create database tables first.

To define your custom records, you subclass the ready-made Record class, or you extend your structs and classes with protocols that come with focused sets of features: fetching methods, persistence methods, record comparison…

Extending structs with record protocols is more "swifty". Subclassing the Record class is more "classic". You can choose either way. See some examples of record definitions, and the list of record methods for an overview.

:point_up: Note: if you are familiar with Core Data’s NSManagedObject or Realm’s Object, you may experience a cultural shock: GRDB records are not uniqued, do not auto-update, and do not lazy-load. This is both a purpose, and a consequence of protocol-oriented programming. You should read How to build an iOS application with SQLite and GRDB.swift for a general introduction.

bulb: Tip: after you have read this chapter, check the Good Practices for Designing Record Types Guide.

bulb: Tip: see the Demo Application for a sample app that uses records.

Overview

Protocols and the Record Class

Records in a Glance

Inserting Records

To insert a record in the database, call the insert method:

let player = Player(name: "Arthur", email: "[email protected]")
try player.insert(db)

:point_right: insert is available for subclasses of the Record class, and types that adopt the [PersistableRecord] protocol.

Fetching Records

To fetch records from the database, call a fetching method:

let arthur = try Player.fetchOne(db,            // Player?
    "SELECT * FROM players WHERE name = ?",
    arguments: ["Arthur"])

let bestPlayers = try Player                    // [Player]
    .order(Column("score").desc)
    .limit(10)
    .fetchAll(db)

let spain = try Country.fetchOne(db, key: "ES") // Country?
:point_right: Fetching from raw SQL is available for subclasses of the Record class, and types that adopt the [FetchableRecord] protocol.

point_right: Fetching without SQL, using the query interface, is available for subclasses of the Record class, and types that adopt both [FetchableRecord] and [TableRecord] protocol.

Updating Records

To update a record in the database, call the update method:

if let player = try Player.fetchOne(db, key: 1) 
    player.score = 1000
    try player.update(db)
}

It is possible to avoid useless updates:

if let player = try Player.fetchOne(db, key: 1) {
    // does not hit the database if score has not changed
    try player.updateChanges(db) {
        $0.score = 1000
    }
}

For batch updates, execute an SQL query:

try db.execute("UPDATE player SET synchronized = 1")

:point_right: update methods are available for subclasses of the Record class, and types that adopt the [PersistableRecord] protocol.

Deleting Records

To delete a record in the database, call the delete method:

if let player = try Player.fetchOne(db, key: 1) {
    try player.delete(db)
}

You can also delete by primary key, or any unique index:

try Player.deleteOne(db, key: 1)
try Player.deleteOne(db, key: ["email": "[email protected]"])
try Country.deleteAll(db, keys: ["FR", "US"])

For batch deletes, execute an SQL query, or see the query interface:

try Player
    .filter(Column("email") == nil)
    .deleteAll(db)

:point_right: delete methods are available for subclasses of the Record class, and types that adopt the [PersistableRecord] protocol.

Counting Records

To count records, call the fetchCount method:

let playerCount: Int = try Player.fetchCount(db)

let playerWithEmailCount: Int = try Player
    .filter(Column("email") == nil)
    .fetchCount(db)

:point_right: fetchCount is available for subclasses of the Record class, and types that adopt the [TableRecord] protocol.

Details follow:

Record Protocols Overview

GRDB ships with three record protocols. Your own types will adopt one or several of them, according to the abilities you want to extend your types with.

  • [FetchableRecord] is able to decode database rows.

    It is always possible to decode rows without this protocol:

    struct Place { ... }
    try dbQueue.read { db in
        let rows = try Row.fetchAll(db, "SELECT * FROM place")
        let places: [Place] = rows.map { row in
            return Place(
                id: row["id"],
                title: row["title"],
                coordinate: CLLocationCoordinate2D(
                    latitude: row["latitude"],
                    longitude: row["longitude"]))
            )
        }
    }

    But FetchableRecord lets you write code that is easier to read, and more efficient as well, both in terms of performance and memory usage:

    struct Place: FetchableRecord { ... }
    try dbQueue.read { db in
        let places = try Place.fetchAll(db, "SELECT * FROM place")
    }

    :bulb: Tip: FetchableRecord can derive its implementation from the standard Decodable protocol. See [Codable Records] for more information.

    FetchableRecord can decode database rows, but it is not able to build SQL requests for you. For that, you also need TableRecord:

  • [TableRecord] is able to generate SQL queries:

    struct Place: TableRecord { ... }
    // SELECT * FROM place ORDER BY title
    let request = Place.order(Column("title"))

    When a type adopts both TableRecord and FetchableRecord, it can load from those requests:

    struct Place: TableRecord, FetchableRecord { ... }
    try dbQueue.read { db in
        let places = try Place.order(Column("title")).fetchAll(db)
        let paris = try Place.fetchOne(key: 1)
    }
  • [PersistableRecord] is able to write: it can create, update, and delete rows in the database:

    struct Place : PersistableRecord { ... }
    try dbQueue.write { db in
        try Place.delete(db, key: 1)
        try Place(...).insert(db)
    }

    A persistable record can also compare itself against other records, and avoid useless database updates.

    :bulb: Tip: PersistableRecord can derive its implementation from the standard Encodable protocol. See [Codable Records] for more information.

FetchableRecord Protocol

The FetchableRecord protocol grants fetching methods to any type that can be built from a database row:

protocol FetchableRecord {
    /// Row initializer
    init(row: Row)
}

To use FetchableRecord, subclass the Record class, or adopt it explicitly. For example:

struct Place {
    var id: Int64?
    var title: String
    var coordinate: CLLocationCoordinate2D
}

extension Place : FetchableRecord {
    init(row: Row) {
        id = row["id"]
        title = row["title"]
        coordinate = CLLocationCoordinate2D(
            latitude: row["latitude"],
            longitude: row["longitude"])
    }
}

Rows also accept column enums:

extension Place : FetchableRecord {
    enum Columns: String, ColumnExpression {
        case id, title, latitude, longitude
    }

    init(row: Row) {
        id = row[Columns.id]
        title = row[Columns.title]
        coordinate = CLLocationCoordinate2D(
            latitude: row[Columns.latitude],
            longitude: row[Columns.longitude])
    }
}

See column values for more information about the row[] subscript.

When your record type adopts the standard Decodable protocol, you don’t have to provide the implementation for init(row:). See [Codable Records] for more information:

// That's all
struct Player: Decodable, FetchableRecord {
    var id: Int64
    var name: String
    var score: Int
}

FetchableRecord allows adopting types to be fetched from SQL queries:

try Place.fetchCursor(db, "SELECT ...", arguments:...) // A Cursor of Place
try Place.fetchAll(db, "SELECT ...", arguments:...)    // [Place]
try Place.fetchOne(db, "SELECT ...", arguments:...)    // Place?

See fetching methods for information about the fetchCursor, fetchAll and fetchOne methods. See StatementArguments for more information about the query arguments.

:point_up: Note: for performance reasons, the same row argument to init(row:) is reused during the iteration of a fetch query. If you want to keep the row for later use, make sure to store a copy: self.row = row.copy().

point_up: Note: The FetchableRecord.init(row:) initializer fits the needs of most applications. But some application are more demanding than others. When FetchableRecord does not exactly provide the support you need, have a look at the [Beyond FetchableRecord] chapter.

TableRecord Protocol

The TableRecord protocol generates SQL for you. To use TableRecord, subclass the Record class, or adopt it explicitly:

protocol TableRecord {
    static var databaseTableName: String { get }
    static var databaseSelection: [SQLSelectable] { get }
}

The databaseSelection type property is optional, and documented in the [Columns Selected by a Request] chapter.

The databaseTableName type property is the name of a database table. By default, it is derived from the type name:

struct Place: TableRecord { }
print(Place.databaseTableName) // prints "place"

For example:

  • Place: place
  • Country: country
  • PostalAddress: postalAddress
  • HTTPRequest: httpRequest
  • TOEFL: toefl

You can still provide a custom table name:

struct Place: TableRecord {
    static let databaseTableName = "location"
}
print(Place.databaseTableName) // prints "location"

Subclasses of the Record class must always override their superclass’s databaseTableName property:

class Place: Record {
    override class var databaseTableName: String {
        return "place"
    }
}
print(Place.databaseTableName) // prints "place"

When a type adopts both TableRecord and FetchableRecord, it can be fetched using the query interface:

// SELECT * FROM place WHERE name = 'Paris'
let paris = try Place.filter(nameColumn == "Paris").fetchOne(db)

TableRecord can also fetch records by primary key:

try Player.fetchOne(db, key: 1)              // Player?
try Player.fetchAll(db, keys: [1, 2, 3])     // [Player]

try Country.fetchOne(db, key: "FR")          // Country?
try Country.fetchAll(db, keys: ["FR", "US"]) // [Country]

When the table has no explicit primary key, GRDB uses the hidden "rowid" column:

// SELECT * FROM document WHERE rowid = 1
try Document.fetchOne(db, key: 1)            // Document?

For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:

// SELECT * FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
try Citizenship.fetchOne(db, key: ["citizenId": 1, "countryCode": "FR"]) // Citizenship?

PersistableRecord Protocol

GRDB provides two protocols that let adopting types create, update, and delete rows in the database:

protocol MutablePersistableRecord : TableRecord {
    /// Defines the values persisted in the database
    func encode(to container: inout PersistenceContainer)

    /// Optional method that lets your adopting type store its rowID upon
    /// successful insertion. Don't call it directly: it is called for you.
    mutating func didInsert(with rowID: Int64, for column: String?)
}
protocol PersistableRecord : MutablePersistableRecord {
    /// Non-mutating version of the optional didInsert(with:for:)
    func didInsert(with rowID: Int64, for column: String?)
}

Yes, two protocols instead of one. Both grant exactly the same advantages. Here is how you pick one or the other:

  • If your type is a class, choose PersistableRecord. On top of that, implement didInsert(with:for:) if the database table has an auto-incremented primary key.

  • If your type is a struct, and the database table has an auto-incremented primary key, choose MutablePersistableRecord, and implement didInsert(with:for:).

  • Otherwise, choose PersistableRecord, and ignore didInsert(with:for:).

The encode(to:) method defines which values (Bool, Int, String, Date, Swift enums, etc.) are assigned to database columns.

The optional didInsert method lets the adopting type store its rowID after successful insertion, and is only useful for tables that have an auto-incremented primary key. It is called from a protected dispatch queue, and serialized with all database updates.

To use the persistable protocols, subclass the Record class, or adopt one of them explicitly. For example:

extension Place : MutablePersistableRecord {
    /// The values persisted in the database
    func encode(to container: inout PersistenceContainer) {
        container["id"] = id
        container["title"] = title
        container["latitude"] = coordinate.latitude
        container["longitude"] = coordinate.longitude
    }

    // Update id upon successful insertion:
    mutating func didInsert(with rowID: Int64, for column: String?) {
        id = rowID
    }
}

var paris = Place(
    id: nil,
    title: "Paris",
    coordinate: CLLocationCoordinate2D(latitude: 48.8534100, longitude: 2.3488000))

try paris.insert(db)
paris.id   // some value

Persistence containers also accept column enums:

extension Place : MutablePersistableRecord {
    enum Columns: String, ColumnExpression {
        case id, title, latitude, longitude
    }

    func encode(to container: inout PersistenceContainer) {
        container[Columns.id] = id
        container[Columns.title] = title
        container[Columns.latitude] = coordinate.latitude
        container[Columns.longitude] = coordinate.longitude
    }
}

When your record type adopts the standard Encodable protocol, you don’t have to provide the implementation for encode(to:). See [Codable Records] for more information:

// That's all
struct Player: Encodable, MutablePersistableRecord {
    var id: Int64?
    var name: String
    var score: Int

    mutating func didInsert(with rowID: Int64, for column: String?) {
        id = rowID
    }
}

Persistence Methods

Record subclasses and types that adopt [PersistableRecord] are given default implementations for methods that insert, update, and delete:

// Instance methods
try place.save(db)                     // INSERT or UPDATE
try place.insert(db)                   // INSERT
try place.update(db)                   // UPDATE
try place.update(db, columns: ...)     // UPDATE
try place.updateChanges(db, from: ...) // Maybe UPDATE
try place.updateChanges(db) { ... }    // Maybe UPDATE
try place.updateChanges(db)            // Maybe UPDATE (Record class only)
try place.delete(db)                   // DELETE
try place.exists(db)

// Type methods
try Place.deleteAll(db)                    // DELETE
try Place.deleteAll(db, keys:...)          // DELETE
try Place.deleteOne(db, key:...)           // DELETE
  • insert, update, save and delete can throw a DatabaseError.

  • update and updateChanges can also throw a PersistenceError, should the update fail because there is no matching row in the database.

    When saving an object that may or may not already exist in the database, prefer the save method:

  • save makes sure your values are stored in the database.

    It performs an UPDATE if the record has a non-null primary key, and then, if no row was modified, an INSERT. It directly perfoms an INSERT if the record has no primary key, or a null primary key.

    Despite the fact that it may execute two SQL statements, save behaves as an atomic operation: GRDB won’t allow any concurrent thread to sneak in (see concurrency).

  • delete returns whether a database row was deleted or not.

All primary keys are supported, including composite primary keys that span several columns, and the implicit rowid primary key.

Customizing the Persistence Methods

Your custom type may want to perform extra work when the persistence methods are invoked.

For example, it may want to have its UUID automatically set before inserting. Or it may want to validate its values before saving.

When you subclass Record, you simply have to override the customized method, and call super:

class Player : Record {
    var uuid: UUID?

    override func insert(_ db: Database) throws {
        if uuid == nil {
            uuid = UUID()
        }
        try super.insert(db)
    }
}

If you use the raw [PersistableRecord] protocol, use one of the special methods performInsert, performUpdate, performSave, performDelete, or performExists:

struct Link : PersistableRecord {
    var url: URL

    func insert(_ db: Database) throws {
        try validate()
        try performInsert(db)
    }

    func update(_ db: Database, columns: Set<String>) throws {
        try validate()
        try performUpdate(db, columns: columns)
    }

    func validate() throws {
        if url.host == nil {
            throw ValidationError("url must be absolute.")
        }
    }
}
:point_up: Note: the special methods performInsert, performUpdate, etc. are reserved for your custom implementations. Do not use them elsewhere. Do not provide another implementation for those methods.

point_up: Note: it is recommended that you do not implement your own version of the save method. Its default implementation forwards the job to update or insert: these are the methods that may need customization, not save.

Codable Records

Record types that adopt an archival protocol (Codable, Encodable or Decodable) get free database support just by declaring conformance to the desired record protocols:

// Declare a record...
struct Player: Codable, FetchableRecord, PersistableRecord {
    var name: String
    var score: Int
}

// ...and there you go:
try dbQueue.write { db in
    try Player(name: "Arthur", score: 100).insert(db)
    let players = try Player.fetchAll(db)
}

Codable records encode and decode their properties according to their own implementation of the Encodable and Decodable protocols. Yet databases have specific requirements:

  • Properties are always coded according to their preferred database representation, when they have one (all values that adopt the DatabaseValueConvertible protocol).
  • You can customize the encoding and decoding of dates and uuids.
  • Complex properties (arrays, dictionaries, nested structs, etc.) are stored as JSON.

For more information about Codable records, see:

:bulb: Tip: see the Demo Application for a sample app that uses Codable records.

JSON Columns

When a Codable record contains a property that is not a simple value (Bool, Int, String, Date, Swift enums, etc.), that value is encoded and decoded as a JSON string. For example:

enum AchievementColor: String, Codable {
    case bronze, silver, gold
}

struct Achievement: Codable {
    var name: String
    var color: AchievementColor
}

struct Player: Codable, FetchableRecord, PersistableRecord {
    var name: String
    var score: Int
    var achievements: [Achievement] // stored in a JSON column
}

try! dbQueue.write { db in
    // INSERT INTO player (name, score, achievements)
    // VALUES (
    //   'Arthur',
    //   100,
    //   '[{"color":"gold","name":"Use Codable Records"}]')
    let achievement = Achievement(name: "Use Codable Records", color: .gold)
    let player = Player(name: "Arthur", score: 100, achievements: [achievement])
    try player.insert(db)
}

GRDB uses the standard JSONDecoder and JSONEncoder from Foundation. By default, Data values are handled with the .base64 strategy, Date with the .millisecondsSince1970 strategy, and non conforming floats with the .throw strategy.

You can customize the JSON format by implementing those methods:

protocol FetchableRecord {
    static func databaseJSONDecoder(for column: String) -> JSONDecoder
}

protocol MutablePersistableRecord {
    static func databaseJSONEncoder(for column: String) -> JSONEncoder
}

:bulb: Tip: Make sure you set the JSONEncoder sortedKeys option, available from iOS 11.0+, macOS 10.13+, and watchOS 4.0+. This option makes sure that the JSON output is stable. This stability is required for [Record Comparison] to work as expected, and database observation tools such as [ValueObservation] to accurately recognize changed records.

Date and UUID Coding Strategies

By default, [Codable Records] encode and decode their Date and UUID properties as described in the general Date and DateComponents and UUID chapters.

To sum up: dates encode themselves in the "YYYY-MM-DD HH:MM:SS.SSS" format, in the UTC time zone, and decode a variety of date formats and timestamps. UUIDs encode themselves as 16-bytes data blobs, and decode both 16-bytes data blobs and strings such as "E621E1F8-C36C-495A-93FC-0C247A3E6E5F".

Those behaviors can be overridden:

protocol FetchableRecord {
    static var databaseDateDecodingStrategy: DatabaseDateDecodingStrategy { get }
}

protocol MutablePersistableRecord {
    static var databaseDateEncodingStrategy: DatabaseDateEncodingStrategy { get }
    static var databaseUUIDEncodingStrategy: DatabaseUUIDEncodingStrategy { get }
}

See DatabaseDateDecodingStrategy, DatabaseDateEncodingStrategy, and DatabaseUUIDEncodingStrategy to learn about all available strategies.

:point_up: Note: there is no customization of uuid decoding, because UUID can already decode all its encoded variants (16-bytes blobs, and uuid strings).

The userInfo Dictionary

Your [Codable Records] can be stored in the database, but they may also have other purposes. In this case, you may need to customize their implementations of Decodable.init(from:) and Encodable.encode(to:), depending on the context.

The standard way to provide such context is the userInfo dictionary. Implement those properties:

protocol FetchableRecord {
    static var databaseDecodingUserInfo: [CodingUserInfoKey: Any] { get }
}

protocol MutablePersistableRecord {
    static var databaseEncodingUserInfo: [CodingUserInfoKey: Any] { get }
}

For example, here is a Player type that customizes its decoding:

// A key that holds a decoder's name
let decoderName = CodingUserInfoKey(rawValue: "decoderName")!

struct Player: FetchableRecord, Decodable {
    init(from decoder: Decoder) throws {
        // Print the decoder name
        let decoderName = decoder.userInfo[decoderName] as? String
        print("Decoded from (decoderName ?? "unknown decoder")")
        ...
    }
}

You can have a specific decoding from JSON…

// prints "Decoded from JSON"
let decoder = JSONDecoder()
decoder.userInfo = [decoderName: "JSON"]
let player = try decoder.decode(Player.self, from: jsonData)

… and another one from database rows:

extension Player: FetchableRecord {
    static let databaseDecodingUserInfo: [CodingUserInfoKey: Any] = [decoderName: "database row"]
}

// prints "Decoded from database row"
let player = try Player.fetchOne(db, ...)

:point_up: Note: make sure the databaseDecodingUserInfo and databaseEncodingUserInfo properties are explicitly declared as [CodingUserInfoKey: Any]. If they are not, the Swift compiler may silently miss the protocol requirement, resulting in sticky empty userInfo.

Tip: Use Coding Keys as Columns

If you declare an explicit CodingKeys enum (what is this?), you can instruct GRDB to use those coding keys as database columns:

struct Player: Codable, FetchableRecord, PersistableRecord {
    var name: String
    var score: Int

    // Add ColumnExpression conformance
    private enum CodingKeys: String, CodingKey, ColumnExpression {
        case name, score
    }
}

This allows your record to build requests with the query interface:

extension Player {
    static func filter(name: String) -> QueryInterfaceRequest<Player> {
        return filter(CodingKeys.name == name)
    }

    static var maximumScore: QueryInterfaceRequest<Int> {
        return select(max(CodingKeys.score), as: Int.self)
    }
}

Those requests can both fetch…

// Fetch values
try dbQueue.read { db in
    // SELECT * FROM player WHERE name = 'Arthur'
    let arthur = try Player.filter(name: "Arthur").fetchOne(db) // Player?

    // SELECT MAX(score) FROM player
    let maxScore = try Player.maximumScore.fetchOne(db)         // Int?
}

… and feed database observation tools such as [ValueObservation]:

// Observe changes
try ValueObservation
    .trackingOne(Player.maximumScore)
    .start(in: dbQueue) { maxScore: Int? in
        print("The maximum score has changed")
    }

Record Class

Record is a class that is designed to be subclassed. It inherits its features from the FetchableRecord, TableRecord, and PersistableRecord protocols. On top of that, Record instances can compare against previous versions of themselves in order to avoid useless updates.

Record subclasses define their custom database relationship by overriding database methods. For example:

class Place: Record {
    var id: Int64?
    var title: String
    var isFavorite: Bool
    var coordinate: CLLocationCoordinate2D

    init(id: Int64?, title: String, isFavorite: Bool, coordinate: CLLocationCoordinate2D) {
        self.id = id
        self.title = title
        self.isFavorite = isFavorite
        self.coordinate = coordinate
        super.init()
    }

    /// The table name
    override class var databaseTableName: String {
        return "place"
    }

    /// The table columns
    enum Columns: String, ColumnExpression {
        case id, title, favorite, latitude, longitude
    }

    /// Creates a record from a database row
    required init(row: Row) {
        id = row[Columns.id]
        title = row[Columns.title]
        isFavorite = row[Columns.favorite]
        coordinate = CLLocationCoordinate2D(
            latitude: row[Columns.latitude],
            longitude: row[Columns.longitude])
        super.init(row: row)
    }

    /// The values persisted in the database
    override func encode(to container: inout PersistenceContainer) {
        container[Columns.id] = id
        container[Columns.title] = title
        container[Columns.favorite] = isFavorite
        container[Columns.latitude] = coordinate.latitude
        container[Columns.longitude] = coordinate.longitude
    }

    /// Update record ID after a successful insertion
    override func didInsert(with rowID: Int64, for column: String?) {
        id = rowID
    }
}

Record Comparison

Records that adopt a [PersistableRecord] protocol can compare against other records, or against previous versions of themselves.

This helps avoiding costly UPDATE statements when a record has not been edited.

The updateChanges Methods

The updateChanges methods perform a database update of the changed columns only (and does nothing if record has no change).

  • updateChanges(_:from:)

    This method lets you compare two records:

    if let oldPlayer = try Player.fetchOne(db, key: 42) {
        var newPlayer = oldPlayer
        newPlayer.score = 100
        if try newPlayer.updateChanges(db, from: oldPlayer) {
            print("player was modified, and updated in the database")
        } else {
            print("player was not modified, and database was not hit")
        }
    }
  • updateChanges(_:with:)

    This method lets you update a record in place:

    if var player = try Player.fetchOne(db, key: 42) {
        let modified = player.updateChanges(db) {
            $0.score = 100
        }
        if modified {
            print("player was modified, and updated in the database")
        } else {
            print("player was not modified, and database was not hit")
        }
    }
  • updateChanges(_:) (Record class only)

    Instances of the Record class are able to compare against themselves, and know if they have changes that have not been saved since the last fetch or saving:

    // Record class only
    if let player = try Player.fetchOne(db, key: 42) {
        player.score = 100
        if try player.updateChanges(db) {
            print("player was modified, and updated in the database")
        } else {
            print("player was not modified, and database was not hit")
        }
    }

The databaseEquals Method

This method returns whether two records have the same database representation:

let oldPlayer: Player = ...
var newPlayer: Player = ...
if newPlayer.databaseEquals(oldPlayer) == false {
    try newPlayer.save(db)
}

:point_up: Note: The comparison is performed on the database representation of records. As long as your record type adopts a PersistableRecord protocol, you don’t need to care about Equatable.

The databaseChanges and hasDatabaseChanges Methods

databaseChanges(from:) returns a dictionary of differences between two records:

let oldPlayer = Player(id: 1, name: "Arthur", score: 100)
let newPlayer = Player(id: 1, name: "Arthur", score: 1000)
for (column, oldValue) in newPlayer.databaseChanges(from: oldPlayer) {
    print("(column) was (oldValue)")
}
// prints "score was 100"

The Record class is able to compare against itself:

// Record class only
let player = Player(id: 1, name: "Arthur", score: 100)
try player.insert(db)
player.score = 1000
for (column, oldValue) in player.databaseChanges {
    print("(column) was (oldValue)")
}
// prints "score was 100"

Record instances also have a hasDatabaseChanges property:

// Record class only
player.score = 1000
if player.hasDatabaseChanges {
    try player.save(db)
}

Record.hasDatabaseChanges is false after a Record instance has been fetched or saved into the database. Subsequent modifications may set it, or not: hasDatabaseChanges is based on value comparison. Setting a property to the same value does not set the changed flag:

let player = Player(name: "Barbara", score: 750)
player.hasDatabaseChanges // true

try player.insert(db)
player.hasDatabaseChanges // false

player.name = "Barbara"
player.hasDatabaseChanges // false

player.score = 1000
player.hasDatabaseChanges // true
player.databaseChanges    // ["score": 750]

For an efficient algorithm which synchronizes the content of a database table with a JSON payload, check JSONSynchronization.playground.

Record Customization Options

GRDB records come with many default behaviors, that are designed to fit most situations. Many of those defaults can be customized for your specific needs:

  • [Customizing the Persistence Methods]: define what happens when you call a persistance method such as player.insert(db)
  • [Conflict Resolution]: Run INSERT OR REPLACE queries, and generally define what happens when a persistence method violates a unique index.
  • [The Implicit RowID Primary Key]: all about the special rowid column.
  • [Columns Selected by a Request]: define which columns are selected by requests such as Player.fetchAll(db).
  • [Beyond FetchableRecord]: the FetchableRecord protocol is not the end of the story.

[Codable Records] have a few extra options:

  • [JSON Columns]: control the format of JSON columns.
  • [Date and UUID Coding Strategies]: control the format of Date and UUID properties in your Codable records.
  • [The userInfo Dictionary]: adapt your Codable implementation for the database.

Conflict Resolution

Insertions and updates can create conflicts: for example, a query may attempt to insert a duplicate row that violates a unique index.

Those conflicts normally end with an error. Yet SQLite let you alter the default behavior, and handle conflicts with specific policies. For example, the INSERT OR REPLACE statement handles conflicts with the "replace" policy which replaces the conflicting row instead of throwing an error.

The five different policies are: abort (the default), replace, rollback, fail, and ignore.

SQLite let you specify conflict policies at two different places:

  • In the definition of the database table:

    // CREATE TABLE player (
    //     id INTEGER PRIMARY KEY AUTOINCREMENT,
    //     email TEXT UNIQUE ON CONFLICT REPLACE
    // )
    try db.create(table: "player") { t in
        t.autoIncrementedPrimaryKey("id")
        t.column("email", .text).unique(onConflict: .replace) // <--
    }
    
    // Despite the unique index on email, both inserts succeed.
    // The second insert replaces the first row:
    try db.execute("INSERT INTO player (email) VALUES (?)", arguments: ["[email protected]"])
    try db.execute("INSERT INTO player (email) VALUES (?)", arguments: ["[email protected]"])
  • In each modification query:

    // CREATE TABLE player (
    //     id INTEGER PRIMARY KEY AUTOINCREMENT,
    //     email TEXT UNIQUE
    // )
    try db.create(table: "player") { t in
        t.autoIncrementedPrimaryKey("id")
        t.column("email", .text).unique()
    }
    
    // Again, despite the unique index on email, both inserts succeed.
    try db.execute("INSERT OR REPLACE INTO player (email) VALUES (?)", arguments: ["[email protected]"])
    try db.execute("INSERT OR REPLACE INTO player (email) VALUES (?)", arguments: ["[email protected]"])

When you want to handle conflicts at the query level, specify a custom persistenceConflictPolicy in your type that adopts the PersistableRecord protocol. It will alter the INSERT and UPDATE queries run by the insert, update and save persistence methods:

protocol MutablePersistableRecord {
    /// The policy that handles SQLite conflicts when records are
    /// inserted or updated.
    ///
    /// This property is optional: its default value uses the ABORT
    /// policy for both insertions and updates, so that GRDB generate
    /// regular INSERT and UPDATE queries.
    static var persistenceConflictPolicy: PersistenceConflictPolicy { get }
}

struct Player : MutablePersistableRecord {
    static let persistenceConflictPolicy = PersistenceConflictPolicy(
        insert: .replace,
        update: .replace)
}

// INSERT OR REPLACE INTO player (...) VALUES (...)
try player.insert(db)

:point_up: Note: the ignore policy does not play well at all with the didInsert method which notifies the rowID of inserted records. Choose your poison:

  • if you specify the ignore policy in the database table definition, don’t implement the didInsert method: it will be called with some random id in case of failed insert.
  • if you specify the ignore policy at the query level, the didInsert method is never called.

:point_up: Note: The replace policy may have to delete rows so that inserts and updates can succeed. Those deletions are not reported to transaction observers (this might change in a future release of SQLite).

The Implicit RowID Primary Key

All SQLite tables have a primary key. Even when the primary key is not explicit:

// No explicit primary key
try db.create(table: "event") { t in
    t.column("message", .text)
    t.column("date", .datetime)
}

// No way to define an explicit primary key
try db.create(virtualTable: "book", using: FTS4()) { t in
    t.column("title")
    t.column("author")
    t.column("body")
}

The implicit primary key is stored in the hidden column rowid. Hidden means that SELECT * does not select it, and yet it can be selected and queried: SELECT *, rowid ... WHERE rowid = 1.

Some GRDB methods will automatically use this hidden column when a table has no explicit primary key:

// SELECT * FROM event WHERE rowid = 1
let event = try Event.fetchOne(db, key: 1)

// DELETE FROM book WHERE rowid = 1
try Book.deleteOne(db, key: 1)

Exposing the RowID Column

By default, a record type that wraps a table without any explicit primary key doesn’t know about the hidden rowid column.

Without primary key, records don’t have any identity, and the persistence method can behave in undesired fashion: update() throws errors, save() always performs insertions and may break constraints, exists() is always false.

When SQLite won’t let you provide an explicit primary key (as in full-text tables, for example), you may want to make your record type fully aware of the hidden rowid column:

  1. Have the databaseSelection static property (from the [TableRecord] protocol) return the hidden rowid column:

    struct Event : TableRecord {
        static let databaseSelection: [SQLSelectable] = [AllColumns(), Column.rowID]
    }
    
    // When you subclass Record, you need an override:
    class Book : Record {
        override class var databaseSelection: [SQLSelectable] {
            return [AllColums(), Column.rowID]
        }
    }

    GRDB will then select the rowid column by default:

    // SELECT *, rowid FROM event
    let events = try Event.fetchAll(db)
  2. Have init(row:) from the [FetchableRecord] protocol consume the "rowid" column:

    struct Event : FetchableRecord {
        var id: Int64?
    
        init(row: Row) {
            id = row[Column.rowID]
        }
    }

    Your fetched records will then know their ids:

    let event = try Event.fetchOne(db)!
    event.id // some value
  3. Encode the rowid in encode(to:), and keep it in the didInsert(with:for:) method (both from the PersistableRecord and MutablePersistableRecord protocols):

    struct Event : MutablePersistableRecord {
        var id: Int64?
    
        func encode(to container: inout PersistenceContainer) {
            container[Column.rowID] = id
            container["message"] = message
            container["date"] = date
        }
    
        mutating func didInsert(with rowID: Int64, for column: String?) {
            id = rowID
        }
    }

    You will then be able to track your record ids, update them, or check for their existence:

    let event = Event(message: "foo", date: Date())
    
    // Insertion sets the record id:
    try event.insert(db)
    event.id // some value
    
    // Record can be updated:
    event.message = "bar"
    try event.update(db)
    
    // Record knows if it exists:
    event.exists(db) // true

Beyond FetchableRecord

Some GRDB users eventually discover that the [FetchableRecord] protocol does not fit all situations. Use cases that are not well handled by FetchableRecord include:

  • Your application needs polymorphic row decoding: it decodes some type or another, depending on the values contained in a database row.

  • Your application needs to decode rows with a context: each decoded value should be initialized with some extra value that does not come from the database.

  • Your application needs a record type that supports untrusted databases, and may fail at decoding database rows (throw an error when a row contains invalid values).

Since those use cases are not well handled by FetchableRecord, don’t try to implement them on top of this protocol: you’ll just fight the framework.

Instead, please have a look at the CustomizedDecodingOfDatabaseRows playground. You’ll run some sample code, and learn how to escape FetchableRecord when you need. And remember that leaving FetchableRecord will not deprive you of query interface requests and generally all SQL generation features of the [TableRecord] and [PersistableRecord] protocols.

Examples of Record Definitions

We will show below how to declare a record type for the following database table:

try dbQueue.write { db in
    try db.create(table: "place") { t in
        t.autoIncrementedPrimaryKey("id")
        t.column("title", .text).notNull()
        t.column("favorite", .boolean).notNull().defaults(to: false)
        t.column("longitude", .double).notNull()
        t.column("latitude", .double).notNull()
    }
}

Each one of the three examples below is correct. You will pick one or the other depending on your personal preferences and the requirements of your application:

Define a Codable struct, and adopt the record protocols you need

This is the shortest way to define a record type.

See the [Record Protocols Overview](#record-protocols-overview), and [Codable Records] for more information.

“`swift
struct Place: Codable {
var id: Int64?
var title: String
var favorite: Bool
var latitude: CLLocationDegrees
var longitude: CLLocationDegrees

var coordinate: CLLocationCoordinate2D {
get {
return CLLocationCoordinate2D(
latitude: latitude,
longitude: longitude)
}
set {
latitude = newValue.latitude
longitude = newValue.longitude
}
}
}

// SQL generation
extension Place: TableRecord { }

// Fetching methods
extension Place: FetchableRecord { }

// Persistence methods
extension Place: MutablePersistableRecord {
/// Update record ID after a successful insertion
mutating func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
“`

Define a plain struct, and adopt the record protocols you need

See the [Record Protocols Overview](#record-protocols-overview) for more information.

“`swift
struct Place {
var id: Int64?
var title: String
var isFavorite: Bool
var coordinate: CLLocationCoordinate2D
}

// SQL generation
extension Place: TableRecord {
/// The table columns
enum Columns: String, ColumnExpression {
case id, title, favorite, latitude, longitude
}
}

// Fetching methods
extension Place: FetchableRecord {
/// Creates a record from a database row
init(row: Row) {
id = row[Columns.id]
title = row[Columns.title]
isFavorite = row[Columns.favorite]
coordinate = CLLocationCoordinate2D(
latitude: row[Columns.latitude],
longitude: row[Columns.longitude])
}
}

// Persistence methods
extension Place: MutablePersistableRecord {
/// The values persisted in the database
func encode(to container: inout PersistenceContainer) {
container[Columns.id] = id
container[Columns.title] = title
container[Columns.favorite] = isFavorite
container[Columns.latitude] = coordinate.latitude
container[Columns.longitude] = coordinate.longitude
}

/// Update record ID after a successful insertion
mutating func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
“`

Subclass the Record class

See the [Record class](#record-class) for more information.

“`swift
class Place: Record {
var id: Int64?
var title: String
var isFavorite: Bool
var coordinate: CLLocationCoordinate2D

init(id: Int64?, title: String, isFavorite: Bool, coordinate: CLLocationCoordinate2D) {
self.id = id
self.title = title
self.isFavorite = isFavorite
self.coordinate = coordinate
super.init()
}

/// The table name
override class var databaseTableName: String {
return “place”
}

/// The table columns
enum Columns: String, ColumnExpression {
case id, title, favorite, latitude, longitude
}

/// Creates a record from a database row
required init(row: Row) {
id = row[Columns.id]
title = row[Columns.title]
isFavorite = row[Columns.favorite]
coordinate = CLLocationCoordinate2D(
latitude: row[Columns.latitude],
longitude: row[Columns.longitude])
super.init(row: row)
}

/// The values persisted in the database
override func encode(to container: inout PersistenceContainer) {
container[Columns.id] = id
container[Columns.title] = title
container[Columns.favorite] = isFavorite
container[Columns.latitude] = coordinate.latitude
container[Columns.longitude] = coordinate.longitude
}

/// Update record ID after a successful insertion
override func didInsert(with rowID: Int64, for column: String?) {
id = rowID
}
}
“`

List of Record Methods

This is the list of record methods, along with their required protocols. The Record class adopts all these protocols, and adds a few extra methods.

Method Protocols Notes
Core Methods
init(row:) [FetchableRecord]
Type.databaseTableName [TableRecord]
Type.databaseSelection [TableRecord] *
Type.persistenceConflictPolicy [PersistableRecord] *
record.encode(to:) [PersistableRecord]
record.didInsert(with:for:) [PersistableRecord]
Insert and Update Records
record.insert(db) [PersistableRecord]
record.save(db) [PersistableRecord]
record.update(db) [PersistableRecord]
record.update(db, columns:...) [PersistableRecord]
record.updateChanges(db, from:...) [PersistableRecord] *
record.updateChanges(db) { ... } [PersistableRecord] *
record.updateChanges(db) Record *
Delete Records
record.delete(db) [PersistableRecord]
Type.deleteOne(db, key:...) [PersistableRecord] ¹
Type.deleteAll(db) [PersistableRecord]
Type.deleteAll(db, keys:...) [PersistableRecord] ¹
Type.filter(...).deleteAll(db) [PersistableRecord] ²
Check Record Existence
record.exists(db) [PersistableRecord]
Convert Record to Dictionary
record.databaseDictionary [PersistableRecord]
Count Records
Type.fetchCount(db) [TableRecord]
Type.filter(...).fetchCount(db) [TableRecord] ²
Fetch Record Cursors
Type.fetchCursor(db) [FetchableRecord] & [TableRecord]
Type.fetchCursor(db, keys:...) [FetchableRecord] & [TableRecord] ¹
Type.fetchCursor(db, sql) [FetchableRecord] ³
Type.fetchCursor(statement) [FetchableRecord]
Type.filter(...).fetchCursor(db) [FetchableRecord] & [TableRecord] ²
Fetch Record Arrays
Type.fetchAll(db) [FetchableRecord] & [TableRecord]
Type.fetchAll(db, keys:...) [FetchableRecord] & [TableRecord] ¹
Type.fetchAll(db, sql) [FetchableRecord] ³
Type.fetchAll(statement) [FetchableRecord]
Type.filter(...).fetchAll(db) [FetchableRecord] & [TableRecord] ²
Fetch Individual Records
Type.fetchOne(db) [FetchableRecord] & [TableRecord]
Type.fetchOne(db, key:...) [FetchableRecord] & [TableRecord] ¹
Type.fetchOne(db, sql) [FetchableRecord] ³
Type.fetchOne(statement) [FetchableRecord]
Type.filter(...).fetchOne(db) [FetchableRecord] & [TableRecord] ²
[Record Comparison]
record.databaseEquals(...) [PersistableRecord]
record.databaseChanges(from:...) [PersistableRecord]
record.updateChanges(db, from:...) [PersistableRecord]
record.updateChanges(db) { ... } [PersistableRecord]
record.hasDatabaseChanges Record
record.databaseChanges Record
record.updateChanges(db) Record

¹ All unique keys are supported: primary keys (single-column, composite, implicit RowID) and unique indexes:

try Player.fetchOne(db, key: 1)                               // Player?
try Player.fetchOne(db, key: ["email": "[email protected]"]) // Player?
try Country.fetchAll(db, keys: ["FR", "US"])                  // [Country]

² See Fetch Requests:

let request = Player.filter(emailColumn != nil).order(nameColumn)
let players = try request.fetchAll(db)  // [Player]
let count = try request.fetchCount(db)  // Int

³ See SQL queries:

let player = try Player.fetchOne("SELECT * FROM player WHERE id = ?", arguments: [1]) // Player?

See Prepared Statements:

let statement = try db.makeSelectStatement("SELECT * FROM player WHERE id = ?")
let player = try Player.fetchOne(statement, arguments: [1])  // Player?

The Query Interface

The query interface lets you write pure Swift instead of SQL:

try dbQueue.write { db in
    // Update database schema
    try db.create(table: "wine") { t in ... }

    // Fetch records
    let wines = try Wine.filter(origin == "Burgundy").order(price).fetchAll(db)

    // Count
    let count = try Wine.filter(color == Color.red).fetchCount(db)

    // Delete
    try Wine.filter(corked == true).deleteAll(db)
}

You need to open a database connection before you can query the database.

Please bear in mind that the query interface can not generate all possible SQL queries. You may also prefer writing SQL, and this is just OK. From little snippets to full queries, your SQL skills are welcome:

try dbQueue.write { db in
    // Update database schema (with SQL)
    try db.execute("CREATE TABLE wine (...)")

    // Fetch records (with SQL)
    let wines = try Wine.fetchAll(db,
        "SELECT * FROM wine WHERE origin = ? ORDER BY price",
        arguments: ["Burgundy"])

    // Count (with an SQL snippet)
    let count = try Wine
        .filter(sql: "color = ?", arguments: [Color.red])
        .fetchCount(db)

    // Delete (with SQL)
    try db.execute("DELETE FROM wine WHERE corked")
}

So don’t miss the SQL API.

Database Schema

Once granted with a database connection, you can setup your database schema without writing SQL:

Create Tables

// CREATE TABLE place (
//   id INTEGER PRIMARY KEY AUTOINCREMENT,
//   title TEXT,
//   favorite BOOLEAN NOT NULL DEFAULT 0,
//   latitude DOUBLE NOT NULL,
//   longitude DOUBLE NOT NULL
// )
try db.create(table: "place") { t in
    t.autoIncrementedPrimaryKey("id")
    t.column("title", .text)
    t.column("favorite", .boolean).notNull().defaults(to: false)
    t.column("longitude", .double).notNull()
    t.column("latitude", .double).notNull()
}

The create(table:) method covers nearly all SQLite table creation features. For virtual tables, see Full-Text Search, or use raw SQL.

SQLite itself has many reference documents about table creation: CREATE TABLE, Datatypes In SQLite Version 3, SQLite Foreign Key Support, ON CONFLICT, The WITHOUT ROWID Optimization.

Configure table creation:

// CREATE TABLE example ( ... )
try db.create(table: "example") { t in ... }

// CREATE TEMPORARY TABLE example IF NOT EXISTS (
try db.create(table: "example", temporary: true, ifNotExists: true) { t in

:bulb: Tip: database table names should be singular, and camel-cased. Make them look like Swift identifiers: place, country, postalAddress, ‘httpRequest’.

This will help you using [Associations] when you need them. Database table names that follow another naming convention are totally OK, but you will need to perform extra configuration.

Add regular columns with their name and eventual type (text, integer, double, numeric, boolean, blob, date and datetime) – see SQLite data types:

// CREATE TABLE example (
//   a,
//   name TEXT,
//   creationDate DATETIME,
try db.create(table: "example") { t in
    t.column("a")
    t.column("name", .text)
    t.column("creationDate", .datetime)

Define not null columns, and set default values:

    // email TEXT NOT NULL,
    t.column("email", .text).notNull()

    // name TEXT NOT NULL DEFAULT 'Anonymous',
    t.column("name", .text).notNull().defaults(to: "Anonymous")

Use an individual column as primary, unique, or foreign key. When defining a foreign key, the referenced column is the primary key of the referenced table (unless you specify otherwise):

    // id INTEGER PRIMARY KEY AUTOINCREMENT,
    t.autoIncrementedPrimaryKey("id")

    // uuid TEXT PRIMARY KEY,
    t.column("uuid", .text).primaryKey()

    // email TEXT UNIQUE,
    t.column("email", .text).unique()

    // countryCode TEXT REFERENCES country(code) ON DELETE CASCADE,
    t.column("countryCode", .text).references("country", onDelete: .cascade)

:bulb: Tip: when you need an integer primary key that automatically generates unique values, it is highly recommended that you use the autoIncrementedPrimaryKey method:

try db.create(table: "example") { t in
    t.autoIncrementedPrimaryKey("id")
    ...
}

The reason for this recommendation is that auto-incremented primary keys prevent the reuse of ids. This prevents your app or database observation tools to think that a row was updated, when it was actually deleted, then replaced. Depending on your application needs, this may be acceptable. But usually it is not.

Create an index on the column:

    t.column("score", .integer).indexed()

For extra index options, see Create Indexes below.

Perform integrity checks on individual columns, and SQLite will only let conforming rows in. In the example below, the $0 closure variable is a column which lets you build any SQL expression.

    // name TEXT CHECK (LENGTH(name) > 0)
    // score INTEGER CHECK (score > 0)
    t.column("name", .text).check { length($0) > 0 }
    t.column("score", .integer).check(sql: "score > 0")

Other table constraints can involve several columns:

    // PRIMARY KEY (a, b),
    t.primaryKey(["a", "b"])

    // UNIQUE (a, b) ON CONFLICT REPLACE,
    t.uniqueKey(["a", "b"], onConfict: .replace)

    // FOREIGN KEY (a, b) REFERENCES parents(c, d),
    t.foreignKey(["a", "b"], references: "parents")

    // CHECK (a + b < 10),
    t.check(Column("a") + Column("b") < 10)

    // CHECK (a + b < 10)
    t.check(sql: "a + b < 10")
}

Modify Tables

SQLite lets you rename tables, and add columns to existing tables:

// ALTER TABLE referer RENAME TO referrer
try db.rename(table: "referer", to: "referrer")

// ALTER TABLE player ADD COLUMN url TEXT
try db.alter(table: "player") { t in
    t.add(column: "url", .text)
}

:point_up: Note: SQLite restricts the possible table alterations, and may require you to recreate dependent triggers or views. See the documentation of the ALTER TABLE for details. See Advanced Database Schema Changes for a way to lift restrictions.

Drop Tables

Drop tables with the drop(table:) method:

try db.drop(table: "obsolete")

Create Indexes

Create indexes with the create(index:) method:

// CREATE UNIQUE INDEX byEmail ON users(email)
try db.create(index: "byEmail", on: "users", columns: ["email"], unique: true)

Relevant SQLite documentation:

Requests

The query interface requests let you fetch values from the database:

let request = Player.filter(emailColumn != nil).order(nameColumn)
let players = try request.fetchAll(db)  // [Player]
let count = try request.fetchCount(db)  // Int

All requests start from a type that adopts the TableRecord protocol, such as a Record subclass (see Records):

class Player : Record { ... }

Declare the table columns that you want to use for filtering, or sorting:

let idColumn = Column("id")
let nameColumn = Column("name")

You can also declare column enums, if you prefer:

// Columns.id and Columns.name can be used just as
// idColumn and nameColumn declared above.
enum Columns: String, ColumnExpression {
    case id
    case name
}

You can now build requests with the following methods: all, none, select, distinct, filter, matching, group, having, order, reversed, limit, joining, including. All those methods return another request, which you can further refine by applying another method: Player.select(...).filter(...).order(...).

  • all(), none(): the requests for all rows, or no row.

    // SELECT * FROM player
    Player.all()

    The hidden rowid column can be selected as well when you need it.

  • select(...) and select(..., as:) define the selected columns. See [Columns Selected by a Request].

    // SELECT name FROM player
    Player.select(nameColumn, as: String.self)
  • annotated(with: ...) extends the selection with association aggregates.

    // SELECT team.*, COUNT(DISTINCT player.rowid) AS playerCount
    // FROM team
    // LEFT JOIN player ON player.teamId = team.id
    // GROUP BY team.id
    Team.annotated(with: Team.players.count)
  • distinct() performs uniquing.

    // SELECT DISTINCT name FROM player
    Player.select(nameColumn, as: String.self).distinct()
  • filter(expression) applies conditions.

    // SELECT * FROM player WHERE id IN (1, 2, 3)
    Player.filter([1,2,3].contains(idColumn))
    
    // SELECT * FROM player WHERE (name IS NOT NULL) AND (height > 1.75)
    Player.filter(nameColumn != nil && heightColumn > 1.75)
  • filter(key:) and filter(keys:) apply conditions on primary keys and unique keys:

    // SELECT * FROM player WHERE id = 1
    Player.filter(key: 1)
    
    // SELECT * FROM country WHERE isoCode IN ('FR', 'US')
    Country.filter(keys: ["FR", "US"])
    
    // SELECT * FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
    Citizenship.filter(key: ["citizenId": 1, "countryCode": "FR"])
    
    // SELECT * FROM player WHERE email = '[email protected]'
    Player.filter(key: ["email": "[email protected]"])
  • matching(pattern) performs full-text search.

    // SELECT * FROM document WHERE document MATCH 'sqlite database'
    let pattern = FTS3Pattern(matchingAllTokensIn: "SQLite database")
    Document.matching(pattern)

    When the pattern is nil, no row will match.

  • group(expression, ...) groups rows.

    // SELECT name, MAX(score) FROM player GROUP BY name
    Player
        .select(nameColumn, max(scoreColumn))
        .group(nameColumn)
  • having(expression) applies conditions on grouped rows.

    // SELECT team, MAX(score) FROM player GROUP BY team HAVING MIN(score) >= 1000
    Player
        .select(teamColumn, max(scoreColumn))
        .group(teamColumn)
        .having(min(scoreColumn) >= 1000)
  • having(aggregate) applies conditions on grouped rows, according to an association aggregate.

    // SELECT team.*
    // FROM team
    // LEFT JOIN player ON player.teamId = team.id
    // GROUP BY team.id
    // HAVING COUNT(DISTINCT player.rowid) >= 5
    Team.having(Team.players.count >= 5)
  • order(ordering, ...) sorts.

    // SELECT * FROM player ORDER BY name
    Player.order(nameColumn)
    
    // SELECT * FROM player ORDER BY score DESC, name
    Player.order(scoreColumn.desc, nameColumn)

    Each order call clears any previous ordering:

    // SELECT * FROM player ORDER BY name
    Player.order(scoreColumn).order(nameColumn)
  • orderByPrimaryKey() sorts by primary key:

    // SELECT * FROM player ORDER BY id
    Player.orderByPrimaryKey()
    
    // SELECT * FROM country ORDER BY code
    Country.orderByPrimaryKey()
    
    // SELECT * FROM citizenship ORDER BY citizenId, countryCode
    Citizenship.orderByPrimaryKey()
  • reversed() reverses the eventual orderings.

    // SELECT * FROM player ORDER BY score ASC, name DESC
    Player.order(scoreColumn.desc, nameColumn).reversed()

    If no ordering was already specified, this method has no effect:

    // SELECT * FROM player
    Player.all().reversed()
  • limit(limit, offset: offset) limits and pages results.

    // SELECT * FROM player LIMIT 5
    Player.limit(5)
    
    // SELECT * FROM player LIMIT 5 OFFSET 10
    Player.limit(5, offset: 10)
  • joining(...) and including(...) fetch and join records through [Associations].

    // SELECT player.*, team.*
    // FROM player
    // JOIN team ON team.id = player.teamId
    Player.including(required: Player.team)

You can refine requests by chaining those methods:

// SELECT * FROM player WHERE (email IS NOT NULL) ORDER BY name
Player.order(nameColumn).filter(emailColumn != nil)

The select, order, group, and limit methods ignore and replace previously applied selection, orderings, grouping, and limits. On the opposite, filter, matching, and having methods extend the query:

Player                          // SELECT * FROM player
    .filter(nameColumn != nil)  // WHERE (name IS NOT NULL)
    .filter(emailColumn != nil) //        AND (email IS NOT NULL)
    .order(nameColumn)          // - ignored -
    .reversed()                 // - ignored -
    .order(scoreColumn)         // ORDER BY score
    .limit(20, offset: 40)      // - ignored -
    .limit(10)                  // LIMIT 10

Raw SQL snippets are also accepted, with eventual arguments:

// SELECT DATE(creationDate), COUNT(*) FROM player WHERE name = 'Arthur' GROUP BY date(creationDate)
Player
    .select(sql: "DATE(creationDate), COUNT(*)")
    .filter(sql: "name = ?", arguments: ["Arthur"])
    .group(sql: "DATE(creationDate)")

Columns Selected by a Request

By default, query interface requests select all columns:

// SELECT * FROM player
let request = Player.all()

The selection can be changed for each individual requests, or for all requests built from a given type.

The select(...) and select(..., as:) methods change the selection of a single request (see [Fetching from Requests] for detailed information):

let request = Player.select(max(Column("score")))
let maxScore: Int? = try Int.fetchOne(db, request)

The default selection for a record type is controlled by the databaseSelection property:

struct RestrictedPlayer : TableRecord {
    static let databaseTableName = "player"
    static let databaseSelection: [SQLSelectable] = [Column("id"), Column("name")]
}

struct ExtendedPlayer : TableRecord {
    static let databaseTableName = "player"
    static let databaseSelection: [SQLSelectable] = [AllColumns(), Column.rowID]
}

// SELECT id, name FROM player
let request = RestrictedPlayer.all()

// SELECT *, rowid FROM player
let request = ExtendedPlayer.all()

:point_up: Note: make sure the databaseSelection property is explicitly declared as [SQLSelectable]. If it is not, the Swift compiler may silently miss the protocol requirement, resulting in sticky SELECT * requests. To verify your setup, see the How do I print a request as SQL? FAQ.

Expressions

Feed requests with SQL expressions built from your Swift code:

SQL Operators

  • =, <>, <, <=, >, >=, IS, IS NOT

    Comparison operators are based on the Swift operators ==, !=, ===, !==, <, <=, >, >=:

    // SELECT * FROM player WHERE (name = 'Arthur')
    Player.filter(nameColumn == "Arthur")
    
    // SELECT * FROM player WHERE (name IS NULL)
    Player.filter(nameColumn == nil)
    
    // SELECT * FROM player WHERE (score IS 1000)
    Player.filter(scoreColumn === 1000)
    
    // SELECT * FROM rectangle WHERE width < height
    Rectangle.filter(widthColumn < heightColumn)

    :point_up: Note: SQLite string comparison, by default, is case-sensitive and not Unicode-aware. See string comparison if you need more control.

  • *, /, +, -

    SQLite arithmetic operators are derived from their Swift equivalent:

    // SELECT ((temperature * 1.8) + 32) AS farenheit FROM planet
    Planet.select((temperatureColumn * 1.8 + 32).aliased("farenheit"))

    :point_up: Note: an expression like nameColumn + "rrr" will be interpreted by SQLite as a numerical addition (with funny results), not as a string concatenation.

  • AND, OR, NOT

    The SQL logical operators are derived from the Swift &&, || and !:

    // SELECT * FROM player WHERE ((NOT verified) OR (score < 1000))
    Player.filter(!verifiedColumn || scoreColumn < 1000)

    When you want to join a sequence of expressions with AND or OR operators, use joined(operator:):

    // SELECT * FROM player WHERE (verified AND (score >= 1000) AND (name IS NOT NULL))
    let conditions = [
        verifiedColumn,
        scoreColumn >= 1000,
        nameColumn != nil]
    Player.filter(conditions.joined(operator: .and))

    When the sequence is empty, joined(operator: .and) returns true, and joined(operator: .or) returns false:

    // SELECT * FROM player WHERE 1
    Player.filter([].joined(operator: .and))
    
    // SELECT * FROM player WHERE 0
    Player.filter([].joined(operator: .or))
  • BETWEEN, IN, NOT IN

    To check inclusion in a Swift sequence (array, set, range…), call the contains method:

    // SELECT * FROM player WHERE id IN (1, 2, 3)
    Player.filter([1, 2, 3].contains(idColumn))
    
    // SELECT * FROM player WHERE id NOT IN (1, 2, 3)
    Player.filter(![1, 2, 3].contains(idColumn))
    
    // SELECT * FROM player WHERE score BETWEEN 0 AND 1000
    Player.filter((0...1000).contains(scoreColumn))
    
    // SELECT * FROM player WHERE (score >= 0) AND (score < 1000)
    Player.filter((0..<1000).contains(scoreColumn))
    
    // SELECT * FROM player WHERE initial BETWEEN 'A' AND 'N'
    Player.filter(("A"..."N").contains(initialColumn))
    
    // SELECT * FROM player WHERE (initial >= 'A') AND (initial < 'N')
    Player.filter(("A"..<"N").contains(initialColumn))

    :point_up: Note: SQLite string comparison, by default, is case-sensitive and not Unicode-aware. See string comparison if you need more control.

  • LIKE

    The SQLite LIKE operator is available as the like method:

    // SELECT * FROM player WHERE (email LIKE '%@example.com')
    Player.filter(emailColumn.like("%@example.com"))

    :point_up: Note: the SQLite LIKE operator is case-insensitive but not Unicode-aware. For example, the expression 'a' LIKE 'A' is true but 'æ' LIKE 'Æ' is false.

  • MATCH

    The full-text MATCH operator is available through FTS3Pattern (for FTS3 and FTS4 tables) and FTS5Pattern (for FTS5):

    FTS3 and FTS4:

    let pattern = FTS3Pattern(matchingAllTokensIn: "SQLite database")
    
    // SELECT * FROM document WHERE document MATCH 'sqlite database'
    Document.matching(pattern)
    
    // SELECT * FROM document WHERE content MATCH 'sqlite database'
    Document.filter(contentColumn.match(pattern))

    FTS5:

    let pattern = FTS5Pattern(matchingAllTokensIn: "SQLite database")
    
    // SELECT * FROM document WHERE document MATCH 'sqlite database'
    Document.matching(pattern)

SQL Functions

  • ABS, AVG, COUNT, LENGTH, MAX, MIN, SUM:

    Those are based on the abs, average, count, length, max, min and sum Swift functions:

    // SELECT MIN(score), MAX(score) FROM player
    Player.select(min(scoreColumn), max(scoreColumn))
    
    // SELECT COUNT(name) FROM player
    Player.select(count(nameColumn))
    
    // SELECT COUNT(DISTINCT name) FROM player
    Player.select(count(distinct: nameColumn))
  • IFNULL

    Use the Swift ?? operator:

    // SELECT IFNULL(name, 'Anonymous') FROM player
    Player.select(nameColumn ?? "Anonymous")
    
    // SELECT IFNULL(name, email) FROM player
    Player.select(nameColumn ?? emailColumn)
  • LOWER, UPPER

    The query interface does not give access to those SQLite functions. Nothing against them, but they are not unicode aware.

    Instead, GRDB extends SQLite with SQL functions that call the Swift built-in string functions capitalized, lowercased, uppercased, localizedCapitalized, localizedLowercased and localizedUppercased:

    Player.select(nameColumn.uppercased())

    :point_up: Note: When comparing strings, you’d rather use a collation:

    let name: String = ...
    
    // Not recommended
    nameColumn.uppercased() == name.uppercased()
    
    // Better
    nameColumn.collating(.caseInsensitiveCompare) == name
  • Custom SQL functions and aggregates

    You can apply your own custom SQL functions and aggregates:

    let f = DatabaseFunction("f", ...)
    
    // SELECT f(name) FROM player
    Player.select(f.apply(nameColumn))

Fetching from Requests

Once you have a request, you can fetch the records at the origin of the request:

// Some request based on `Player`
let request = Player.filter(...)... // QueryInterfaceRequest<Player>

// Fetch players:
try request.fetchCursor(db) // A Cursor of Player
try request.fetchAll(db)    // [Player]
try request.fetchOne(db)    // Player?

For example:

let allPlayers = try Player.fetchAll(db)                            // [Player]
let arthur = try Player.filter(nameColumn == "Arthur").fetchOne(db) // Player?

See fetching methods for information about the fetchCursor, fetchAll and fetchOne methods.

You sometimes want to fetch other values.

The simplest way is to use the request as an argument to a fetching method of the desired type:

// Fetch an Int
let request = Player.select(max(scoreColumn))
let maxScore = try Int.fetchOne(db, request) // Int?

// Fetch a Row
let request = Player.select(min(scoreColumn), max(scoreColumn))
let row = try Row.fetchOne(db, request)!     // Row
let minScore = row[0] as Int?
let maxScore = row[1] as Int?

When you also want to use database observation tools such as [ValueObservation], you have to go one step further, and change the type of the request:

  • When you change the selection, prefer the select(..., as:) method:

    // A request of Int
    let request = Player.select(max(scoreColumn), as: Int.self)
    
    // Simple fetch
    let maxScore = try dbQueue.read { db in
        try request.fetchOne(db) // Int?
    }
    
    // Observe with ValueObservation
    try ValueObservation
        .trackingOne(request)
        .start(in: dbQueue) { maxScore: Int? in
            print("The maximum score has changed")
        }
  • Otherwise, use asRequest(of:). Here is an example that uses [Associations]:

    struct BookInfo: FetchableRecord, Decodable {
        var book: Book
        var author: Author
    }
    
    // A request of BookInfo
    let request = Book
        .including(required: Book.author)
        .asRequest(of: BookInfo.self)
    
    // Simple fetch
    let bookInfos = try dbQueue.read { db in
        try request.fetchAll(db) // [BookInfo]
    }
    
    // Observe with ValueObservation
    try ValueObservation
        .trackingAll(request)
        .start(in: dbQueue) { bookInfos: [BookInfo] in
            print("Books have changed")
        }

Fetching By Key

Fetching records according to their primary key is a very common task. It has a shortcut which accepts any single-column primary key:

// SELECT * FROM player WHERE id = 1
try Player.fetchOne(db, key: 1)              // Player?

// SELECT * FROM player WHERE id IN (1, 2, 3)
try Player.fetchAll(db, keys: [1, 2, 3])     // [Player]

// SELECT * FROM country WHERE isoCode = 'FR'
try Country.fetchOne(db, key: "FR")          // Country?

// SELECT * FROM country WHERE isoCode IN ('FR', 'US')
try Country.fetchAll(db, keys: ["FR", "US"]) // [Country]

When the table has no explicit primary key, GRDB uses the hidden "rowid" column:

// SELECT * FROM document WHERE rowid = 1
try Document.fetchOne(db, key: 1)            // Document?

For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:

// SELECT * FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
try Citizenship.fetchOne(db, key: ["citizenId": 1, "countryCode": "FR"]) // Citizenship?

// SELECT * FROM player WHERE email = '[email protected]'
try Player.fetchOne(db, key: ["email": "[email protected]"])              // Player?

When you want to build a request and plan to fetch from it later, use the filter(key:) and filter(keys:) methods:

// SELECT * FROM player WHERE id = 1
let request = Player.filter(key: 1)
let player = try request.fetchOne(db)    // Player?

// SELECT * FROM player WHERE id IN (1, 2, 3)
let request = Player.filter(keys: [1, 2, 3])
let players = try request.fetchAll(db)   // [Player]

// SELECT * FROM country WHERE isoCode = 'FR'
let request = Country.filter(key: "FR")
let country = try request.fetchOne(db)   // Country?

// SELECT * FROM country WHERE isoCode IN ('FR', 'US')
let request = Country.filter(keys: ["FR", "US"])
let countries = try request.fetchAll(db) // [Country]

// SELECT * FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
let request = Citizenship.filter(key: ["citizenId": 1, "countryCode": "FR"])
let citizenship = request.fetchOne(db)   // Citizenship?

// SELECT * FROM player WHERE email = '[email protected]'
let request = Player.filter(key: ["email": "[email protected]"])
let player = try request.fetchOne(db)    // Player?

Those requests can feed [ValueObservation]:

try ValueObservation.
    .trackingOne(Player.filter(key: 1))
    .start(in: dbQueue) { player: Player? in
        print("Player 1 has changed")
    }

Fetching Aggregated Values

Requests can count. The fetchCount() method returns the number of rows that would be returned by a fetch request:

// SELECT COUNT(*) FROM player
let count = try Player.fetchCount(db) // Int

// SELECT COUNT(*) FROM player WHERE email IS NOT NULL
let count = try Player.filter(emailColumn != nil).fetchCount(db)

// SELECT COUNT(DISTINCT name) FROM player
let count = try Player.select(nameColumn).distinct().fetchCount(db)

// SELECT COUNT(*) FROM (SELECT DISTINCT name, score FROM player)
let count = try Player.select(nameColumn, scoreColumn).distinct().fetchCount(db)

Other aggregated values can also be selected and fetched (see SQL Functions):

let request = Player.select(max(scoreColumn))
let maxScore = try Int.fetchOne(db, request) // Int?

let request = Player.select(min(scoreColumn), max(scoreColumn))
let row = try Row.fetchOne(db, request)!     // Row
let minScore = row[0] as Int?
let maxScore = row[1] as Int?

Delete Requests

Requests can delete records, with the deleteAll() method:

// DELETE FROM player WHERE email IS NULL
let request = Player.filter(emailColumn == nil)
try request.deleteAll(db)

:point_up: Note Deletion methods are only available for records that adopts the [PersistableRecord] protocol.

Deleting records according to their primary key is also quite common. It has a shortcut which accepts any single-column primary key:

// DELETE FROM player WHERE id = 1
try Player.deleteOne(db, key: 1)

// DELETE FROM player WHERE id IN (1, 2, 3)
try Player.deleteAll(db, keys: [1, 2, 3])

// DELETE FROM country WHERE isoCode = 'FR'
try Country.deleteOne(db, key: "FR")

// DELETE FROM country WHERE isoCode IN ('FR', 'US')
try Country.deleteAll(db, keys: ["FR", "US"])

When the table has no explicit primary key, GRDB uses the hidden "rowid" column:

// DELETE FROM document WHERE rowid = 1
try Document.deleteOne(db, key: 1)

For multiple-column primary keys and unique keys defined by unique indexes, provide a dictionary:

// DELETE FROM citizenship WHERE citizenId = 1 AND countryCode = 'FR'
try Citizenship.deleteOne(db, key: ["citizenId": 1, "countryCode": "FR"])

// DELETE FROM player WHERE email = '[email protected]'
Player.deleteOne(db, key: ["email": "[email protected]"])

Custom Requests

Until now, we have seen requests created from any type that adopts the [TableRecord] protocol:

let request = Player.all()  // QueryInterfaceRequest<Player>

Those requests of type QueryInterfaceRequest can fetch and count:

try request.fetchCursor(db) // A Cursor of Player
try request.fetchAll(db)    // [Player]
try request.fetchOne(db)    // Player?
try request.fetchCount(db)  // Int

When the query interface can not generate the SQL you need, you can still fallback to raw SQL:

// Custom SQL is always welcome
try Player.fetchAll(db, "SELECT ...")   // [Player]

But you may prefer to bring some elegance back in, and build custom requests:

// No custom SQL in sight
try Player.customRequest().fetchAll(db) // [Player]

Custom requests can also feed [ValueObservation]:

try ValueObservation.
    .trackingAll(Player.customRequest(...))
    .start(in: dbQueue) { players: [Player] in
        print("Players have changed")
    }

FetchRequest Protocol

FetchRequest is the protocol for all requests that run from a single select statement, and know how fetched rows should be interpreted:

protocol FetchRequest: DatabaseRegionConvertible {
    /// The type that tells how fetched rows should be decoded
    associatedtype RowDecoder

    /// A tuple that contains a prepared statement, and an eventual row adapter.
    func prepare(_ db: Database) throws -> (SelectStatement, RowAdapter?)

    /// The number of rows fetched by the request.
    func fetchCount(_ db: Database) throws -> Int
}

When the RowDecoder associated type is Row, or a value, or a type that conforms to [FetchableRecord], the request can fetch: see Fetching From Custom Requests below.

The prepare method returns a prepared statement and an optional row adapter. The prepared statement tells which SQL query should be executed. The row adapter helps presenting the fetched rows in the way expected by the row decoders (see row adapter).

The fetchCount method has a default implementation that builds a correct but naive SQL query from the statement returned by prepare: SELECT COUNT(*) FROM (...). Adopting types can refine the counting SQL by customizing their fetchCount implementation.

The base DatabaseRegionConvertible protocol is involved in database observation. For more information, see [DatabaseRegion], [DatabaseRegionObservation], and [ValueObservation].

The FetchRequest protocol is adopted, for example, by query interface requests:

// A FetchRequest whose RowDecoder associated type is Player:
let request = Player.all()

Building Custom Requests

To build custom requests, you can use one of the built-in requests, derive requests from other requests, or create your own request type that adopts the FetchRequest protocol.

  • SQLRequest is a fetch request built from raw SQL. For example:

    extension Player {
        static func filter(color: Color) -> SQLRequest<Player> {
            return SQLRequest<Player>(
                "SELECT * FROM player WHERE color = ?"
                arguments: [color])
        }
    }
    
    // [Player]
    try Player.filter(color: .red).fetchAll(db)
  • The asRequest(of:) method changes the type fetched by the request. It is useful, for example, when you use [Associations]:

    struct BookInfo: FetchableRecord, Decodable {
        var book: Book
        var author: Author
    }
    
    let request = Book
        .including(required: Book.author)
        .asRequest(of: BookInfo.self)
    
    // [BookInfo]
    try request.fetchAll(db)
  • The adapted(_:) method eases the consumption of complex rows with row adapters. See Joined Queries Support for some sample code that uses this method.

  • AnyFetchRequest: a type-erased request.

Fetching From Custom Requests

A type adopting FetchRequest knows exactly what it has to do when its RowDecoder associated type can decode database rows (Row itself, values, or [FetchableRecord]):

let rowRequest = ...        // Some FetchRequest that fetches Row
try request.fetchCursor(db) // A cursor of rows

let playerRequest = ...     // Some FetchRequest that fetches Player
try request.fetchAll(db)    // [Player]

let intRequest = ...        // Some FetchRequest that fetches Int
try request.fetchOne(db)    // Int?

For example:

let playerRequest = SQLRequest<Player>(
    "SELECT * FROM player WHERE color = ?"
    arguments: [color])
try request.fetchAll(db)    // [Player]

See fetching methods for information about the fetchCursor, fetchAll and fetchOne methods.

The RowDecoder type associated with the FetchRequest does not have to be Row, DatabaseValueConvertible, or FetchableRecord. See the [Beyond FetchableRecord] chapter for more information.

Migrations

Migrations are a convenient way to alter your database schema over time in a consistent and easy way.

Migrations run in order, once and only once. When a user upgrades your application, only non-applied migrations are run.

Inside each migration, you typically define and update your database tables according to your evolving application needs:

var migrator = DatabaseMigrator()

// 1st migration
migrator.registerMigration("v1") { db in
    try db.create(table: "author") { t in ... }
    try db.create(table: "book") { t in ... }
    try db.create(index: ...)
}

// 2nd migration
migrator.registerMigration("v2") { db in
    try db.alter(table: "author") { t in ... }
}

// Migrations for future versions will be inserted here:
//
// // 3rd migration
// migrator.registerMigration("...") { db in
//     ...
// }

Each migration runs in a separate transaction. Should one throw an error, its transaction is rollbacked, subsequent migrations do not run, and the error is eventually thrown by migrator.migrate(dbQueue).

The memory of applied migrations is stored in the database itself (in a reserved table).

You migrate the database up to the latest version with the migrate(_:) method:

try migrator.migrate(dbQueue) // or migrator.migrate(dbPool)

To migrate a database up to a specific version, use migrate(_:upTo:):

try migrator.migrate(dbQueue, upTo: "v2")

Migrations can only run forward:

try migrator.migrate(dbQueue, upTo: "v2")
try migrator.migrate(dbQueue, upTo: "v1")
// fatal error: database is already migrated beyond migration "v1"

Check if a migration has been applied:

let appliedMigrations = try migrator.appliedMigrations(in: dbQueue)
if appliedMigrations.contains("v2") {
    // "v2" migration has been applied
}

The eraseDatabaseOnSchemaChange Option

A DatabaseMigrator can automatically wipe out the full database content, and recreate the whole database from scratch, if it detects that a migration has changed its definition:

var migrator = DatabaseMigrator()
migrator.eraseDatabaseOnSchemaChange = true

Beware! This flag can destroy your precious users’ data!

Yet it may be useful in those two situations:

  1. During application development, as you are still designing migrations, and the schema changes often.

    In this case, it is recommended that this flag does not ship in the distributed application:

    var migrator = DatabaseMigrator()
    #if DEBUG
    // Speed up development by nuking the database when migrations change
    migrator.eraseDatabaseOnSchemaChange = true
    #endif
  2. When the database content can easily be recreated, such as a cache for some downloaded data.

The eraseDatabaseOnSchemaChange option triggers a recreation of the database if the migrator detects a schema change. A schema change is any difference in the sqlite_master table, which contains the SQL used to create database tables, indexes, triggers, and views.

Advanced Database Schema Changes

SQLite does not support many schema changes, and won’t let you drop a table column with "ALTER TABLE … DROP COLUMN …", for example.

Yet any kind of schema change is still possible. The SQLite documentation explains in detail how to do so: https://www.sqlite.org/lang_altertable.html#otheralter. This technique requires the temporary disabling of foreign key checks, and is supported by the registerMigrationWithDeferredForeignKeyCheck function:

// Add a NOT NULL constraint on player.name:
migrator.registerMigrationWithDeferredForeignKeyCheck("AddNotNullCheckOnName") { db in
    try db.create(table: "new_player") { t in
        t.autoIncrementedPrimaryKey("id")
        t.column("name", .text).notNull()
    }
    try db.execute("INSERT INTO new_player SELECT * FROM player")
    try db.drop(table: "player")
    try db.rename(table: "new_player", to: "player")
}

While your migration code runs with disabled foreign key checks, those are re-enabled and checked at the end of the migration, regardless of eventual errors.

Full-Text Search

Full-Text Search is an efficient way to search a corpus of textual documents.

// Create full-text tables
try db.create(virtualTable: "book", using: FTS4()) { t in // or FTS3(), or FTS5()
    t.column("author")
    t.column("title")
    t.column("body")
}

// Populate full-text table with records or SQL
try Book(...).insert(db)
try db.execute(
    "INSERT INTO book (author, title, body) VALUES (?, ?, ?)",
    arguments: [...])

// Build search patterns
let pattern = FTS3Pattern(matchingPhrase: "Moby-Dick")

// Search with the query interface or SQL
let books = try Book.matching(pattern).fetchAll(db)
let books = try Book.fetchAll(db,
    "SELECT * FROM book WHERE book MATCH ?",
    arguments: [pattern])

Choosing the Full-Text Engine

SQLite supports three full-text engines: FTS3, FTS4 and FTS5.

Generally speaking, FTS5 is better than FTS4 which improves on FTS3. But this does not really tell which engine to choose for your application. Instead, make your choice depend on:

  • The full-text features needed by the application:

    Full-Text Needs FTS3 FTS4 FTS5
    :question: Queries
    Words searches (documents that contain "database") X X X
    Prefix searches (documents that contain a word starting with "data") X X X
    Phrases searches (documents that contain the phrase "SQLite database") X X X
    Boolean searches (documents that contain "SQLite" or "database") X X X
    Proximity search (documents that contain "SQLite" near "database") X X X
    :scissors: Tokenization
    Ascii case insensitivity (have "DATABASE" match "database") X X X
    Unicode case insensitivity (have "ÉLÉGANCE" match "élégance") X X X
    Latin diacritics insensitivity (have "elegance" match "élégance") X X X
    English Stemming (have "frustration" match "frustrated") X X X
    English Stemming and Ascii case insensitivity X X X
    English Stemming and Unicode case insensitivity X
    English Stemming and Latin diacritics insensitivity X
    Synonyms (have "1st" match "first") ¹ ¹ X ²
    Pinyin and Romaji (have "romaji" match "ローマ字") ¹ ¹ X ²
    Stop words (don’t index, and don’t match words like "and" and "the") ¹ ¹ X ²
    Spell checking (have "alamaba" match "alabama") ¹ ¹ ¹
    :bowtie: Other Features
    Ranking (sort results by relevance) ¹ ¹ X
    Snippets (display a few words around a match) X X X

    ¹ Requires extra setup, possibly hard to implement.

    ² Requires a custom tokenizer.

    For a full feature list, read the SQLite documentation. Some missing features can be achieved with extra application code.

  • The speed versus disk space constraints. Roughly speaking, FTS4 and FTS5 are faster than FTS3, but use more space. FTS4 only supports content compression.

  • The location of the indexed text in your database schema. Only FTS4 and FTS5 support "contentless" and "external content" tables.

  • The SQLite library integrated in your application. The version of SQLite that ships with iOS, macOS and watchOS supports FTS3 and FTS4 out of the box, but not always FTS5. To use FTS5, see Enabling FTS5 Support.

  • See FST3 vs. FTS4 and FTS5 vs. FTS3/4 for more differences.

:point_up: Note: In case you were still wondering, it is recommended to read the SQLite documentation: FTS3 & FTS4 and FTS5.

Create FTS3 and FTS4 Virtual Tables

FTS3 and FTS4 full-text tables store and index textual content.

Create tables with the create(virtualTable:using:) method:

// CREATE VIRTUAL TABLE document USING fts3(content)
try db.create(virtualTable: "document", using: FTS3()) { t in
    t.column("content")
}

// CREATE VIRTUAL TABLE document USING fts4(content)
try db.create(virtualTable: "document", using: FTS4()) { t in
    t.column("content")
}

All columns in a full-text table contain text. If you need to index a table that contains other kinds of values, you need an "external content" full-text table.

You can specify a tokenizer:

// CREATE VIRTUAL TABLE book USING fts4(
//   tokenize=porter,
//   author,
//   title,
//   body
// )
try db.create(virtualTable: "book", using: FTS4()) { t in
    t.tokenizer = .porter
    t.column("author")
    t.column("title")
    t.column("body")
}

FTS4 supports options:

// CREATE VIRTUAL TABLE book USING fts4(
//   content,
//   uuid,
//   content="",
//   compress=zip,
//   uncompress=unzip,
//   prefix="2,4",
//   notindexed=uuid,
//   languageid=lid
// )
try db.create(virtualTable: "document", using: FTS4()) { t in
    t.content = ""
    t.compress = "zip"
    t.uncompress = "unzip"
    t.prefixes = [2, 4]
    t.column("content")
    t.column("uuid").notIndexed()
    t.column("lid").asLanguageId()
}

The content option is involved in "contentless" and "external content" full-text tables. GRDB can help you defining full-text tables that automatically synchronize with their content table. See External Content Full-Text Tables.

See SQLite documentation for more information.

FTS3 and FTS4 Tokenizers

A tokenizer defines what "matching" means. Depending on the tokenizer you choose, full-text searches won’t return the same results.

SQLite ships with three built-in FTS3/4 tokenizers: simple, porter and unicode61 that use different algorithms to match queries with indexed content:

try db.create(virtualTable: "book", using: FTS4()) { t in
    // Pick one:
    t.tokenizer = .simple // default
    t.tokenizer = .porter
    t.tokenizer = .unicode61(...)
}

See below some examples of matches:

content query simple porter unicode61
Foo Foo X X X
Foo FOO X X X
Jérôme Jérôme X ¹ X ¹ X ¹
Jérôme JÉRÔME X ¹
Jérôme Jerome X ¹
Database Databases X
Frustration Frustrated X

¹ Don’t miss Unicode Full-Text Gotchas

  • simple

    try db.create(virtualTable: "book", using: FTS4()) { t in
        t.tokenizer = .simple   // default
    }

    The default "simple" tokenizer is case-insensitive for ASCII characters. It matches "foo" with "FOO", but not "Jérôme" with "JÉRÔME".

    It does not provide stemming, and won’t match "databases" with "database".

    It does not strip diacritics from latin script characters, and won’t match "jérôme" with "jerome".

  • porter

    try db.create(virtualTable: "book", using: FTS4()) { t in
        t.tokenizer = .porter
    }

    The "porter" tokenizer compares English words according to their roots: it matches "database" with "databases", and "frustration" with "frustrated".

    It does not strip diacritics from latin script characters, and won’t match "jérôme" with "jerome".

  • unicode61

    try db.create(virtualTable: "book", using: FTS4()) { t in
        t.tokenizer = .unicode61()
        t.tokenizer = .unicode61(removeDiacritics: false)
    }

    The "unicode61" tokenizer is case-insensitive for unicode characters. It matches "Jérôme" with "JÉRÔME".

    It strips diacritics from latin script characters by default, and matches "jérôme" with "jerome". This behavior can be disabled, as in the example above.

    It does not provide stemming, and won’t match "databases" with "database".

See SQLite tokenizers for more information.

FTS3Pattern

Full-text search in FTS3 and FTS4 tables is performed with search patterns:

  • database matches all documents that contain "database"
  • data* matches all documents that contain a word starting with "data"
  • SQLite database matches all documents that contain both "SQLite" and "database"
  • SQLite OR database matches all documents that contain "SQLite" or "database"
  • "SQLite database" matches all documents that contain the "SQLite database" phrase

Not all search patterns are valid: they must follow the Full-Text Index Queries Grammar.

The FTS3Pattern type helps you validating patterns, and building valid patterns from untrusted strings (such as strings typed by users):

struct FTS3Pattern {
    init(rawPattern: String) throws
    init?(matchingAnyTokenIn string: String)
    init?(matchingAllTokensIn string: String)
    init?(matchingPhrase string: String)
}

The first initializer validates your raw patterns against the query grammar, and may throw a DatabaseError:

// OK: FTS3Pattern
let pattern = try FTS3Pattern(rawPattern: "sqlite AND database")
// DatabaseError: malformed MATCH expression: [AND]
let pattern = try FTS3Pattern(rawPattern: "AND")

The three other initializers don’t throw. They build a valid pattern from any string, including strings provided by users of your application. They let you find documents that match all given words, any given word, or a full phrase, depending on the needs of your application:

let query = "SQLite database"
// Matches documents that contain "SQLite" or "database"
let pattern = FTS3Pattern(matchingAnyTokenIn: query)
// Matches documents that contain both "SQLite" and "database"
let pattern = FTS3Pattern(matchingAllTokensIn: query)
// Matches documents that contain "SQLite database"
let pattern = FTS3Pattern(matchingPhrase: query)

They return nil when no pattern could be built from the input string:

let pattern = FTS3Pattern(matchingAnyTokenIn: "")  // nil
let pattern = FTS3Pattern(matchingAnyTokenIn: "*") // nil

FTS3Pattern are regular values. You can use them as query arguments:

let documents = try Document.fetchAll(db,
    "SELECT * FROM document WHERE content MATCH ?",
    arguments: [pattern])

Use them in the query interface:

// Search in all columns
let documents = try Document.matching(pattern).fetchAll(db)

// Search in a specific column:
let documents = try Document.filter(Column("content").match(pattern)).fetchAll(db)

Enabling FTS5 Support

When the FTS3 and FTS4 full-text engines don’t suit your needs, you may want to use FTS5. See Choosing the Full-Text Engine to help you make a decision.

The version of SQLite that ships with iOS, macOS and watchOS does not always support the FTS5 engine. To enable FTS5 support, you’ll need to install GRDB with one of those installation techniques:

  1. Use the GRDBPlus CocoaPod. It uses the system SQLite, and requires iOS 11.4+ / macOS 10.13+ / watchOS 4.3+:

    pod 'GRDBPlus'
  2. Use the GRDBCipher CocoaPod. It uses SQLCipher (see encryption), and requires iOS 8.0+ / macOS 10.9+ / watchOS 2.0+:

    pod 'GRDBCipher'
  3. Use a custom SQLite build and activate the SQLITE_ENABLE_FTS5 compilation option.

Create FTS5 Virtual Tables

FTS5 full-text tables store and index textual content.

To use FTS5, you’ll need a custom SQLite build that activates the SQLITE_ENABLE_FTS5 compilation option.

Create FTS5 tables with the create(virtualTable:using:) method:

// CREATE VIRTUAL TABLE document USING fts5(content)
try db.create(virtualTable: "document", using: FTS5()) { t in
    t.column("content")
}

All columns in a full-text table contain text. If you need to index a table that contains other kinds of values, you need an "external content" full-text table.

You can specify a tokenizer:

// CREATE VIRTUAL TABLE book USING fts5(
//   tokenize='porter',
//   author,
//   title,
//   body
// )
try db.create(virtualTable: "book", using: FTS5()) { t in
    t.tokenizer = .porter()
    t.column("author")
    t.column("title")
    t.column("body")
}

FTS5 supports options:

// CREATE VIRTUAL TABLE book USING fts5(
//   content,
//   uuid UNINDEXED,
//   content='table',
//   content_rowid='id',
//   prefix='2 4',
//   columnsize=0,
//   detail=column
// )
try db.create(virtualTable: "document", using: FTS5()) { t in
    t.column("content")
    t.column("uuid").notIndexed()
    t.content = "table"
    t.contentRowID = "id"
    t.prefixes = [2, 4]
    t.columnSize = 0
    t.detail = "column"
}

The content and contentRowID options are involved in "contentless" and "external content" full-text tables. GRDB can help you defining full-text tables that automatically synchronize with their content table. See External Content Full-Text Tables.

See SQLite documentation for more information.

FTS5 Tokenizers

A tokenizer defines what "matching" means. Depending on the tokenizer you choose, full-text searches won’t return the same results.

SQLite ships with three built-in FTS5 tokenizers: ascii, porter and unicode61 that use different algorithms to match queries with indexed content.

try db.create(virtualTable: "book", using: FTS5()) { t in
    // Pick one:
    t.tokenizer = .unicode61() // default
    t.tokenizer = .unicode61(...)
    t.tokenizer = .ascii
    t.tokenizer = .porter(...)
}

See below some examples of matches:

content query ascii unicode61 porter on ascii porter on unicode61
Foo Foo X X X X
Foo FOO X X X X
Jérôme Jérôme X ¹ X ¹ X ¹ X ¹
Jérôme JÉRÔME X ¹ X ¹
Jérôme Jerome X ¹ X ¹
Database Databases X X
Frustration Frustrated X X

¹ Don’t miss Unicode Full-Text Gotchas

  • unicode61

    try db.create(virtualTable: "book", using: FTS5()) { t in
        t.tokenizer = .unicode61()
        t.tokenizer = .unicode61(removeDiacritics: false)
    }

    The default "unicode61" tokenizer is case-insensitive for unicode characters. It matches "Jérôme" with "JÉRÔME".

    It strips diacritics from latin script characters by default, and matches "jérôme" with "jerome". This behavior can be disabled, as in the example above.

    It does not provide stemming, and won’t match "databases" with "database".

  • ascii

    try db.create(virtualTable: "book", using: FTS5()) { t in
        t.tokenizer = .ascii
    }

    The "ascii" tokenizer is case-insensitive for ASCII characters. It matches "foo" with "FOO", but not "Jérôme" with "JÉRÔME".

    It does not provide stemming, and won’t match "databases" with "database".

    It does not strip diacritics from latin script characters, and won’t match "jérôme" with "jerome".

  • porter

    try db.create(virtualTable: "book", using: FTS5()) { t in
        t.tokenizer = .porter()       // porter wrapping unicode61 (the default)
        t.tokenizer = .porter(.ascii) // porter wrapping ascii
        t.tokenizer = .porter(.unicode61(removeDiacritics: false)) // porter wrapping unicode61 without diacritics stripping
    }

    The porter tokenizer is a wrapper tokenizer which compares English words according to their roots: it matches "database" with "databases", and "frustration" with "frustrated".

    It strips diacritics from latin script characters if it wraps unicode61, and does not if it wraps ascii (see the example above).

See SQLite tokenizers for more information, and custom FTS5 tokenizers in order to add your own tokenizers.

FTS5Pattern

Full-text search in FTS5 tables is performed with search patterns:

  • database matches all documents that contain "database"
  • data* matches all documents that contain a word starting with "data"
  • SQLite database matches all documents that contain both "SQLite" and "database"
  • SQLite OR database matches all documents that contain "SQLite" or "database"
  • "SQLite database" matches all documents that contain the "SQLite database" phrase

Not all search patterns are valid: they must follow the Full-Text Query Syntax.

The FTS5Pattern type helps you validating patterns, and building valid patterns from untrusted strings (such as strings typed by users):

extension Database {
    func makeFTS5Pattern(rawPattern: String, forTable table: String) throws -> FTS5Pattern
}

struct FTS5Pattern {
    init?(matchingAnyTokenIn string: String)
    init?(matchingAllTokensIn string: String)
    init?(matchingPhrase string: String)
}

The Database.makeFTS5Pattern(rawPattern:forTable:) method validates your raw patterns against the query grammar and the columns of the targeted table, and may throw a DatabaseError:

// OK: FTS5Pattern
try db.makeFTS5Pattern(rawPattern: "sqlite", forTable: "book")
// DatabaseError: syntax error near "AND"
try db.makeFTS5Pattern(rawPattern: "AND", forTable: "book")
// DatabaseError: no such column: missing
try db.makeFTS5Pattern(rawPattern: "missing: sqlite", forTable: "book")

The FTS5Pattern initializers don’t throw. They build a valid pattern from any string, including strings provided by users of your application. They let you find documents that match all given words, any given word, or a full phrase, depending on the needs of your application:

let query = "SQLite database"
// Matches documents that contain "SQLite" or "database"
let pattern = FTS5Pattern(matchingAnyTokenIn: query)
// Matches documents that contain both "SQLite" and "database"
let pattern = FTS5Pattern(matchingAllTokensIn: query)
// Matches documents that contain "SQLite database"
let pattern = FTS5Pattern(matchingPhrase: query)
// Matches documents that start with "SQLite database"
let pattern = FTS5Pattern(matchingPrefixPhrase: query)

They return nil when no pattern could be built from the input string:

let pattern = FTS5Pattern(matchingAnyTokenIn: "")  // nil
let pattern = FTS5Pattern(matchingAnyTokenIn: "*") // nil

FTS5Pattern are regular values. You can use them as query arguments:

let documents = try Document.fetchAll(db,
    "SELECT * FROM document WHERE document MATCH ?",
    arguments: [pattern])

Use them in the query interface:

let documents = try Document.matching(pattern).fetchAll(db)

FTS5: Sorting by Relevance

FTS5 can sort results by relevance (most to least relevant):

// SQL
let documents = try Document.fetchAll(db,
    "SELECT * FROM document WHERE document MATCH ? ORDER BY rank",
    arguments: [pattern])

// Query Interface
let documents = try Document.matching(pattern).order(Column.rank).fetchAll(db)

For more information about the ranking algorithm, as well as extra options, read Sorting by Auxiliary Function Results

GRDB does not provide any ranking for FTS3 and FTS4. See SQLite’s Search Application Tips if you really need it.

External Content Full-Text Tables

An external content table does not store the indexed text. Instead, it indexes the text stored in another table.

This is very handy when you want to index a table that can not be declared as a full-text table (because it contains non-textual values, for example). You just have to define an external content full-text table that refers to the regular table.

The two tables must be kept up-to-date, so that the full-text index matches the content of the regular table. This synchronization happens automatically if you use the synchronize(withTable:) method in your full-text table definition:

// A regular table
try db.create(table: "book") { t in
    t.column("author", .text)
    t.column("title", .text)
    t.column("content", .text)
    ...
}

// A full-text table synchronized with the regular table
try db.create(virtualTable: "book_ft", using: FTS4()) { t in // or FTS5()
    t.synchronize(withTable: "book")
    t.column("author")
    t.column("title")
    t.column("content")
}

The eventual content already present in the regular table is indexed, and every insert, update or delete that happens in the regular table is automatically applied to the full-text index.

For more information, see the SQLite documentation about external content tables: FTS4, FTS5.

See also WWDC Companion, a sample app that uses external content tables to store, display, and let the user search the WWDC sessions.

Deleting Synchronized Full-Text Tables

Synchronization of full-text tables with their content table happens by the mean of SQL triggers.

SQLite automatically deletes those triggers when the content (not full-text) table is dropped.

However, those triggers remain after the full-text table has been dropped. Unless they are dropped too, they will prevent future insertion, updates, and deletions in the content table, and the creation of a new full-text table.

To drop those triggers, use the dropFTS4SynchronizationTriggers or dropFTS5SynchronizationTriggers methods:

// Create tables
try db.create(table: "book") { t in
    ...
}
try db.create(virtualTable: "book_ft", using: FTS4()) { t in
    t.synchronize(withTable: "book")
    ...
}

// Drop full-text table
try db.drop(table: "book_ft")
try db.dropFTS4SynchronizationTriggers(forTable: "book_ft")

:warning: Warning: there was a bug in GRDB up to version 2.3.1 included, which created triggers with a wrong name. If it is possible that the full-text table was created by an old version of GRDB, then delete the synchronization triggers twice: once with the name of the deleted full-text table, and once with the name of the content table:

// Drop full-text table
try db.drop(table: "book_ft")
try db.dropFTS4SynchronizationTriggers(forTable: "book_ft")
try db.dropFTS4SynchronizationTriggers(forTable: "book") // Support for GRDB <= 2.3.1

Querying External Content Full-Text Tables

When you need to perform a full-text search, and the external content table contains all the data you need, you can simply query the full-text table.

But if you need to load columns from the regular table, and in the same time perform a full-text search, then you will need to query both tables at the same time.

That is because SQLite will throw an error when you try to perform a full-text search on a regular table:

// SQLite error 1: unable to use function MATCH in the requested context
// SELECT * FROM book WHERE book MATCH '...'
let books = Book.matching(pattern).fetchAll(db)

The solution is to perform a joined request, using raw SQL:

let sql = """
    SELECT book.*
    FROM book
    JOIN book_ft
        ON book_ft.rowid = book.rowid
        AND book_ft MATCH ?
    """
let books = Book.fetchAll(db, sql, arguments: [pattern])

Full-Text Records

You can define record types around the full-text virtual tables.

However these tables don’t have any explicit primary key. Instead, they use the implicit rowid primary key: a special hidden column named rowid.

You will have to expose this hidden column in order to fetch, delete, and update full-text records by primary key.

Unicode Full-Text Gotchas

The SQLite built-in tokenizers for FTS3, FTS4 and FTS5 are generally unicode-aware, with a few caveats, and limitations.

Generally speaking, matches may fail when content and query don’t use the same unicode normalization. SQLite actually exhibits inconsistent behavior in this regard.

For example, for "aimé" to match "aimé", they better have the same normalization: the NFC "aimu// Wrong way: this code may discard hundreds of useless database rows
let players = try Player.order(scoreColumn.desc).fetchAll(db)
let hallOfFame = players.prefix(5)

// Better way
let hallOfFame = try Player.order(scoreColumn.desc).limit(5).fetchAll(db)3" form may not match its NFD "aimeu// Wrong way: this code may discard hundreds of useless database rows
let players = try Player.order(scoreColumn.desc).fetchAll(db)
let hallOfFame = players.prefix(5)

// Better way
let hallOfFame = try Player.order(scoreColumn.desc).limit(5).fetchAll(db)2" equivalent. Most strings that you get from Swift, UIKit and Cocoa use NFC, so be careful with NFD inputs (such as strings from the HFS+ file system, or strings that you can’t trust like network inputs). Use String.precomposedStringWithCanonicalMapping to turn a string into NFC.

Besides, if you want "fi" to match the ligature "fi" (U+FB01), then you need to normalize your indexed contents and inputs to NFKC or NFKD. Use String.precomposedStringWithCompatibilityMapping to turn a string into NFKC.

Unicode normalization is not the end of the story, because it won’t help "Encyclopaedia" match "Encyclopædia", "Mueller", "Müller", "Grossmann", "Großmann", or "Diyarbakır", "DIYARBAKIR". The String.applyingTransform method can help.

GRDB lets you write custom FTS5 tokenizers that can transparently deal with all these issues. For FTS3 and FTS4, you’ll need to pre-process your strings before injecting them in the full-text engine.

Happy indexing!

Joined Queries Support

GRDB helps consuming joined queries with complex selection.

In this chapter, we will focus on the extraction of information from complex rows, such as the ones fetched by the query below:

-- How to consume the left, middle, and right parts of those rows?
SELECT player.*, team.*, MAX(round.score) AS maxScore
FROM player
LEFT JOIN team ON ...
LEFT JOIN round ON ...
GROUP BY ...

We will not talk about the generation of joined queries, which is covered in [Associations].

So what are we talking about?

It is difficult to consume rows fetched from complex joined queries, because they often contain several columns with the same name: id from table player, id from table team, etc.

When such ambiguity happens, GRDB row accessors always favor the leftmost matching column. This means that row["id"] would give a player id, whithout any obvious way to access the team id.

A classical technique to avoid this ambiguity is to give each column a unique name. For example:

-- A classical technique
SELECT player.id AS player_id, player.name AS player_name, team.id AS team_id, team.name AS team_name, team.color AS team_color, MAX(round.score) AS maxScore
FROM player
LEFT JOIN team ON ...
LEFT JOIN round ON ...
GROUP BY ...

This technique works pretty well, but it has three drawbacks:

  1. The selection becomes hard to read and understand.
  2. Such queries are difficult to write by hand.
  3. The mangled names are a very bad fit for [FetchableRecord] types that expect specific column names. After all, if the Team record type can read SELECT * FROM team ..., it should be able to read SELECT ..., team.*, ... as well.

We thus need another technique. Below we’ll see how to split rows into slices, and preserve column names.

SELECT player.*, team.*, MAX(round.score) AS maxScore FROM ... will be splitted into three slices: one that contains player’s columns, one that contains team’s columns, and a remaining slice that contains remaining column(s). The Player record type will be able to read the first slice, which contains the colums expected by the Player.init(row:) initializer. In the same way, the Team record type could read the second slice.

Unlike the name-mangling technique, splitting rows keeps SQL legible, accepts your hand-crafted SQL queries, and plays as nicely as possible with your existing record types.

Splitting Rows, an Introduction

Let’s first write some introductory code, hoping that this chapter will make you understand how pieces fall together. We’ll see later how records will help us streamline the initial approach, how to track changes in joined requests, and how we can use the standard Decodable protocol.

To split rows, we will use row adapters. Row adapters adapt rows so that row consumers see exactly the columns they want. Among other things, row adapters can define several row scopes that give access to as many row slices. Sounds like a perfect match.

At the very beginning, there is an SQL query:

try dbQueue.read { db in
    let sql = """
        SELECT player.*, team.*, MAX(round.score) AS maxScore
        FROM player
        LEFT JOIN team ON ...
        LEFT JOIN round ON ...
        GROUP BY ...
        """

We need an adapter that extracts player columns, in a slice that has as many columns as there are columns in the player table. That’s RangeRowAdapter:

    // SELECT player.*, team.*, ...
    //        <------>
    let playerWidth = try db.columns(in: "player").count
    let playerAdapter = RangeRowAdapter(0 ..< playerWidth)

We also need an adapter that extracts team columns:

    // SELECT player.*, team.*, ...
    //                  <---->
    let teamWidth = try db.columns(in: "team").count
    let teamAdapter = RangeRowAdapter(playerWidth ..< (playerWidth + teamWidth))

We merge those two adapters in a single ScopeAdapter that will allow us to access both sliced rows:

    let playerScope = "player"
    let teamScope = "team"
    let adapter = ScopeAdapter([
        playerScope: playerAdapter,
        teamScope: teamAdapter])

And now we can fetch, and start consuming our rows. You already know row cursors:

    let rows = try Row.fetchCursor(db, sql, adapter: adapter)
    while let row = try rows.next() {

From a fetched row, we can build a player:

        let player: Player = row[playerScope]

In the SQL query, the team is joined with the LEFT JOIN operator. This means that the team may be missing: its slice may contain team values, or it may only contain NULLs. When this happens, we don’t want to build a Team record, and we thus load an optional Team:

        let team: Team? = row[teamScope]

And finally, we can load the maximum score, assuming that the "maxScore" column is not ambiguous:

        let maxScore: Int = row["maxScore"]

        print("player: (player)")
        print("team: (team)")
        print("maxScore: (maxScore)")
    }
}

:bulb: In this chapter, we have learned:

  • how to use RangeRowAdapter to extract a specific table’s columns into a row slice.
  • how to use ScopeAdapter to gives access to several row slices through named scopes.
  • how to use Row subscripting to extract records from rows, or optional records in order to deal with left joins.

Splitting Rows, the Record Way

Our introduction above has introduced important techniques. It uses row adapters in order to split rows. It uses Row subscripting in order to extract records from row slices.

But we may want to make it more usable and robust:

  1. It’s generally easier to consume records than raw rows.
  2. Joined records not always need all columns from a table (see TableRecord.databaseSelection in [Columns Selected by a Request]).
  3. Building row adapters is long and error prone.

To address the first bullet, let’s define a record that holds our player, optional team, and maximum score. Since it can decode database rows, it adopts the [FetchableRecord] protocol:

struct PlayerInfo {
    var player: Player
    var team: Team?
    var maxScore: Int
}

/// PlayerInfo can decode rows:
extension PlayerInfo: FetchableRecord {
    private enum Scopes {
        static let player = "player"
        static let team = "team"
    }

    init(row: Row) {
        player = row[Scopes.player]
        team = row[Scopes.team]
        maxScore = row["maxScore"]
    }
}

Let’s now write the method that fetches PlayerInfo records:

extension PlayerInfo {
    static func fetchAll(_ db: Database) throws -> [PlayerInfo] {

To acknowledge that both Player and Team records may customize their selection of the "player" and "team" columns, we’ll write our SQL in a slightly different way:

        // Let Player and Team customize their selection:
        let sql = """
            SELECT
                (Player.selectionSQL()), -- instead of player.*
                (Team.selectionSQL()),   -- instead of team.*
                MAX(round.score) AS maxScore
            FROM player
            LEFT JOIN team ON ...
            LEFT JOIN round ON ...
            GROUP BY ...
            """

Player.selectionSQL() will output player.*, unless Player defines a customized selection.

:point_up: Note: you may also use SQL table aliases:

let sql = """
    SELECT
        (Player.selectionSQL(alias: "p")),
        (Team.selectionSQL(alias: "t")),
        MAX(r.score) AS maxScore
    FROM player p
    LEFT JOIN team t ON ...
    LEFT JOIN round r ON ...
    GROUP BY ...
    """

Now is the time to build adapters (taking in account the customized selection of both player and team). We use the splittingRowAdapters global function, which builds row adapters of desired widths:

        let adapters = try splittingRowAdapters(columnCounts: [
            Player.numberOfSelectedColumns(db),
            Team.numberOfSelectedColumns(db)])

        let adapter = ScopeAdapter([
            Scopes.player: adapters[0],
            Scopes.team: adapters[1]])

:point_up: Note: splittingRowAdapters returns as many adapters as necessary to fully split a row. In the example above, it returns three adapters: one for player, one for team, and one for the remaining columns.

And finally, we can fetch player infos:

        return try PlayerInfo.fetchAll(db, sql, adapter: adapter)
    }
}

And when your app needs to fetch player infos, it now reads:

// Fetch player infos
let playerInfos = try dbQueue.read { db in
    try PlayerInfo.fetchAll(db)
}

:bulb: In this chapter, we have learned:

  • how to define a FetchableRecord record that consumes rows fetched from a joined query.
  • how to use selectionSQL and numberOfSelectedColumns in order to deal with nested record types that define custom selection.
  • how to use splittingRowAdapters in order to streamline the definition of row slices.
  • how to gather all relevant methods and constants in a record type, fully responsible of its relationship with the database.

Splitting Rows, the Request Way

The PlayerInfo.fetchAll method above directly fetches records. It’s all good, but in order to profit from database observation, you’ll need a custom request that defines a database query.

It is recommended that you read the previous paragraphs before you dive in this sample code. We start with the same PlayerInfo record as above:

struct PlayerInfo {
    var player: Player
    var team: Team?
    var maxScore: Int
}

/// PlayerInfo can decode rows:
extension PlayerInfo: FetchableRecord {
    private enum Scopes {
        static let player = "player"
        static let team = "team"
    }

    init(row: Row) {
        player = row[Scopes.player]
        team = row[Scopes.team]
        maxScore = row["maxScore"]
    }
}

Now we write a method that returns a request, and build the fetching method on top of that request:

extension PlayerInfo {
    /// The request for all player infos
    static func all() -> AdaptedFetchRequest<SQLRequest<PlayerInfo>> {
        let sql = """
            SELECT
                (Player.selectionSQL()),
                (Team.selectionSQL()),
                MAX(round.score) AS maxScore
            FROM player
            LEFT JOIN team ON ...
            LEFT JOIN round ON ...
            GROUP BY ...
            """
        return SQLRequest<PlayerInfo>(sql).adapted { db in
            let adapters = try splittingRowAdapters(columnCounts: [
                Player.numberOfSelectedColumns(db),
                Team.numberOfSelectedColumns(db)])
            return ScopeAdapter([
                Scopes.player: adapters[0],
                Scopes.team: adapters[1]])
        }
    }

    /// Fetches all player infos
    static func fetchAll(_ db: Database) throws -> [PlayerInfo] {
        return try all().fetchAll(db)
    }
}

It is now time to use our request:

// Fetch player infos
let playerInfos = try dbQueue.read { db in
    try PlayerInfo.fetchAll(db)
}

// Track player infos with RxRGDB:
PlayerInfo.all()
    .rx.fetchAll(in: dbQueue)
    .subscribe(onNext: { playerInfos: [PlayerInfo] in
        print("Player infos have changed")
    })

:bulb: In this chapter, we have learned how to define a custom request that can both fetch records from joined queries, and feed database observation tools.

Splitting Rows, the Codable Way

[Codable Records] build on top of the standard Decodable protocol in order to decode database rows.

You can consume complex joined queries with Codable records as well. As a demonstration, we’ll rewrite the above sample code:

struct Player: Decodable, FetchableRecord, TableRecord {
    var id: Int64
    var name: String
}
struct Team: Decodable, FetchableRecord, TableRecord {
    var id: Int64
    var name: String
    var color: Color
}
struct PlayerInfo: Decodable, FetchableRecord {
    var player: Player
    var team: Team?
    var maxScore: Int
}

extension PlayerInfo {
    /// The request for all player infos
    static func all() -> AdaptedFetchRequest<SQLRequest<PlayerInfo>> {
        let sql = """
            SELECT
                (Player.selectionSQL()),
                (Team.selectionSQL()),
                MAX(round.score) AS maxScore
            FROM player
            LEFT JOIN team ON ...
            LEFT JOIN round ON ...
            GROUP BY ...
            """
        return SQLRequest<PlayerInfo>(sql).adapted { db in
            let adapters = try splittingRowAdapters(columnCounts: [
                Player.numberOfSelectedColumns(db),
                Team.numberOfSelectedColumns(db)])
            return ScopeAdapter([
                CodingKeys.player.stringValue: adapters[0],
                CodingKeys.team.stringValue: adapters[1]])
        }
    }

    /// Fetches all player infos
    static func fetchAll(_ db: Database) throws -> [PlayerInfo] {
        return try all().fetchAll(db)
    }
}

// Fetch player infos
let playerInfos = try dbQueue.read { db in
    try PlayerInfo.fetchAll(db)
}

// Track player infos with RxRGDB:
PlayerInfo.all()
    .rx.fetchAll(in: dbQueue)
    .subscribe(onNext: { playerInfos: [PlayerInfo] in
        print("Player infos have changed")
    })

:bulb: In this chapter, we have learned how to use the Decodable protocol and its associated CodingKeys enum in order to dry up our code.

Database Changes Observation

SQLite notifies its host application of changes performed to the database, as well of transaction commits and rollbacks.

GRDB puts this SQLite feature to some good use, and lets you observe the database in various ways:

  • After Commit Hook: Handle successful transactions one by one.
  • [ValueObservation and DatabaseRegionObservation]: Automated tracking of database requests.
  • [FetchedRecordsController]: Animate table views according to database changes.
  • TransactionObserver Protocol: Low-level database observation.
  • [RxGRDB]: Automated tracking of database changes, with RxSwift.

Database observation requires that a single database queue or pool is kept open for all the duration of the database usage.

After Commit Hook

When your application needs to make sure a specific database transaction has been successfully committed before it executes some work, use the Database.afterNextTransactionCommit(_:) method.

Its closure argument is called right after database changes have been successfully written to disk:

try dbQueue.write { db in
    db.afterNextTransactionCommit { db in
        print("success")
    }
    ...
} // prints "success"

The closure runs in a protected dispatch queue, serialized with all database updates.

This "after commit hook" helps synchronizing the database with other resources, such as files, or system sensors.

In the example below, a location manager starts monitoring a CLRegion if and only if it has successfully been stored in the database:

/// Inserts a region in the database, and start monitoring upon
/// successful insertion.
func startMonitoring(_ db: Database, region: CLRegion) throws {
    // Make sure database is inside a transaction
    try db.inSavepoint {

        // Save the region in the database
        try insert(...)

        // Start monitoring if and only if the insertion is
        // eventually committed
        db.afterNextTransactionCommit { _ in
            // locationManager prefers the main queue:
            DispatchQueue.main.async {
                locationManager.startMonitoring(for: region)
            }
        }

        return .commit
    }
}

The method above won’t trigger the location manager if the transaction is eventually rollbacked (explicitly, or because of an error), as in the sample code below:

try dbQueue.write { db in
    // success
    try startMonitoring(db, region)

    // On error, the transaction is rollbacked, the region is not inserted, and
    // the location manager is not invoked.
    try failableMethod(db)
}

ValueObservation and DatabaseRegionObservation

ValueObservation and DatabaseRegionObservation are two database observations tools that track changes in database requests.

// Let's observe all players!
let request = Player.all()

[ValueObservation] notifies your application with fresh values (this is what most applications need :+1:):

let observation = ValueObservation.trackingAll(request)
let observer = observation.start(in: dbQueue) { players: [Player]? in
    let names = players.map { $0.name }.joined(separator: ", ")
    print("Fresh players: (names)")
}

try dbQueue.write { db in
    try Player(name: "Arthur").insert(db)
}
// Prints "Fresh players: Arthur, ..."

[DatabaseRegionObservation] notifies your application with database connections, right after an impactful database transaction has been committed (reserved for more advanced use cases :nerd_face:):

let observation = DatabaseRegionObservation(tracking: request)
let observer = observation.start(in: dbQueue) { db: Database in
    print("Player have changed.")
}

try dbQueue.write { db in
    try Player(name: "Barbara").insert(db)
}
// Prints "Players have changed."
  • [ValueObservation]
  • [DatabaseRegionObservation]

ValueObservation

ValueObservation tracks changes in the results of database requests, and notifies fresh values whenever the database changes.

Changes are only notified after they have been committed in the database. No insertion, update, or deletion in tracked tables is missed. This includes indirect changes triggered by foreign keys or SQL triggers.

ValueObservation Usage

Here is a typical UIViewController which observes the database in order to keep its view up-to-date:

class PlayerViewController: UIViewController {
    @IBOutlet weak var nameLabel: UILabel!
    private var observer: TransactionObserver?

    override func viewWillAppear(_ animated: Bool) {
        super.viewWillAppear(animated)

        // Define a ValueObservation which tracks a player
        let request = Player.filter(key: 42)
        let observation = ValueObservation.trackingOne(request)

        // Start observing the database
        observer = try! observation.start(
            in: dbQueue,
            onChange: { [unowned self] player: Player? in
                // Player has changed: update view
                self.nameLabel.text = player?.name
            })
    }

    override func viewWillDisappear(_ animated: Bool) {
        super.viewWillDisappear(animated)

        // Stop observing the database
        observer = nil
    }
}

By default, all values are notified on the main queue. Views can be updated right from the onChange callback.

An initial fetch is performed as soon as the observation starts: the view is set up and ready when the viewWillAppear method returns.

The observer returned by the start method is stored in a property of the view controller. This allows the view controller to control the duration of the observation. When the observer is deallocated, the observation stops. Meanwhile, all transactions that modify the observed player are notified, and the nameLabel is kept up-to-date.

:bulb: Tip: see the Demo Application for a sample app that uses ValueObservation.

ValueObservation.trackingCount, trackingOne, trackingAll

Given a request, you can track its number of results, the first one, or all of them:

ValueObservation.trackingCount(request)
ValueObservation.trackingOne(request)
ValueObservation.trackingAll(request)

Those observations match the fetchCount, fetchOne, and fetchAll request methods:

  • trackingCount notifies counts:

    // Observe number of players
    let observer = ValueObservation
        .trackingCount(Player.all())
        .start(in: dbQueue) { count: Int in
            print("Number of players have changed: (count)")
        }
  • trackingOne notifies optional values, built from a single database row (if any):

    // Observe a single player
    let observer = ValueObservation
        .trackingOne(Player.filter(key: 1))
        .start(in: dbQueue) { player: Player? in
            print("Player has changed: (player)")
        }
    
    // Observe the maximum score
    let request = Player.select(max(Column("score")), as: Int.self)
    let observer = ValueObservation
        .trackingOne(request)
        .start(in: dbQueue) { maximumScore: Int? in
            print("Maximum score has changed: (maximumScore)")
        }
  • trackingAll notifies arrays:

    // Observe all players
    let observer = ValueObservation
        .trackingAll(Player.all())
        .start(in: dbQueue) { players: [Player] in
            print("Players have changed: (players)")
        }
    
    // Observe all player names
    let request = SQLRequest<String>("SELECT name FROM player")
    let observer = ValueObservation
        .trackingAll(request)
        .start(in: dbQueue) { names: [String] in
            print("Player names have changed: (names)")
        }

:point_up: Note: the observations returned by the ValueObservation.trackingCount, trackingOne, and trackingAll methods perform a filtering of consecutive identical values, based on raw database values.

ValueObservation.tracking(_:fetch:)

Observing the database is not always easy to express with simple requests, as above.

For example, let’s say that we have a struct that defines a "Hall of Fame":

struct HallOfFame {
    var totalPlayerCount: Int
    var bestPlayers: [Player]

    /// Fetch a HallOfFame
    static fetch(_ db: Database) throws -> HallOfFame {
        let totalPlayerCount = try Player.fetchCount(db)
        let bestPlayers = try Player
            .order(Column("score").desc)
            .limit(10)
            .fetchAll(db)
        return HallOfFame(
            totalPlayerCount: totalPlayerCount,
            bestPlayers: bestPlayers)
    }
}

let hallOfFame = try dbQueue.read { db in try HallOfFame.fetch(db) }
print("""
    Best players out of (hallOfFame.totalPlayerCount):
    (hallOfFame.bestPlayers)
    """)

In order to track changes in the Hall of Fame, we’ll use the ValueObservation.tracking(_:fetch:) method. It accepts two parameters:

  1. A list of observed requests.
  2. A closure that fetches a fresh value whenever one of the observed requests are modified.

In our case, any change to the player table can impact the Hall of Fame. We thus track the request for all players, Player.all(), and fetch a new Hall of Fame whenever players change:

let observation = ValueObservation.tracking(Player.all(), fetch: { db in
    try HallOfFame.fetch(db)
})

let observer = observation.start(in: dbQueue) { hallOfFame: HallOfFame in
    print("""
        Best players out of (hallOfFame.totalPlayerCount):
        (hallOfFame.bestPlayers)
        """)
}

Filtering out Consecutive Identical Values

It may happen that a database change does not modify the observed values. The Hall of Fame, for example, is not affected by changes that happen to the worst players.

When such a database change happens, ValueObservation.tracking(_:fetch:) is triggered, just in case the best players would be modified, and ends up notifying identical consecutive values.

You can filter out those duplicates with the ValueObservation.distinctUntilChanged method. It requires the observed value to adopt the Equatable protocol:

extension HallOfFame: Equatable { ... }

let observation = ValueObservation
    .tracking(Player.all(), fetch: HallOfFame.fetch)
    .distinctUntilChanged()

let observer = observation.start(in: dbQueue) { hallOfFame: HallOfFame in
    print("""
        Best players out of (hallOfFame.totalPlayerCount):
        (hallOfFame.bestPlayers)
        """)
}

DatabaseRegionConvertible Observation

The initial parameter of the ValueObservation.tracking(_:fetch:) method can be fed with requests, and generally speaking, values that adopt the [DatabaseRegionConvertible] protocol.

Thanks to DatabaseRegionConvertible, TeamInfoRequest below is not only able to fetch a team and its players, but also to be observed.

/// A team and its players
struct TeamInfo {
    var team: Team
    var players: [Player]
}

/// A request that can fetch TeamInfo, given a team id.
struct TeamInfoRequest {
    var teamId: Int64

    /// The request for the team
    private var teamRequest: QueryInterfaceRequest<Team> {
        return Team.filter(key: teamId)
    }

    /// The request for the players
    private var playersRequest: QueryInterfaceRequest<Player> {
        return Player.filter(Column("teamId") == teamId)
    }

    /// Fetch a TeamInfo
    func fetch(_ db: Database) throws -> TeamInfo? {
        guard let team = try teamRequest.fetchOne(db) else {
            return nil
        }
        let players = try playersRequest.fetchAll(db)
        return TeamInfo(team: team, players: players)
    }
}

/// Make TeamInfoRequest observable
extension TeamInfoRequest: DatabaseRegionConvertible {
    func databaseRegion(_ db: Database) throws -> DatabaseRegion {
        // Returns the union of the team region and the players region
        let teamRegion = try teamRequest.databaseRegion(db)
        let playersRegion = try playersRequest.databaseRegion(db)
        return teamRegion.union(playersRegion)
    }
}

let request = TeamInfoRequest(teamId: 1)

// Simple fetch
let teamInfo: TeamInfo? = try dbQueue.read(request.fetch)

// Observation
let observer = ValueObservation
    .tracking(request, fetch: request.fetch)
    .start(in: dbQueue) { teamInfo: TeamInfo? in
        print("Team and its players have hanged.")
    }

ValueObservation Transformations

ValueObservation.map

The map method lets you transform the values notified by a ValueObservation.

For example:

// Observe a player's profile image
let observation = ValueObservation
    .trackingOne(Player.filter(key: 42))
    .map { player in player?.loadBigProfileImage() }

let observer = observation.start(in: dbQueue) { image: UIImage? in
    print("Player picture has changed")
}

The transformation closure does not run on the main queue, and is suitable for heavy computations.

ValueObservation.compactMap

The compactMap method lets you transform and filter the values notified by a ValueObservation. Only non-nil transformed values are notified.

For example:

// Observe a player
let observation = ValueObservation
    .trackingOne(Player.filter(key: 42))
    .compactMap { $0 }

let observer = observation.start(in: dbQueue) { player: Player in
    print("Player name: (player.name)")
}

The transformation closure does not run on the main queue, and is suitable for heavy computations.

ValueObservation.distinctUntilChanged

The distinctUntilChanged method filters out the consecutive equal values notified by a ValueObservation. The observed values must adopt the standard Equatable protocol.

For example:

let observation = ValueObservation
    .trackingOne(Player.filter(key: 42))
    .map { player in player != nil } // existence test
    .distinctUntilChanged()

let observer = observation.start(in: dbQueue) { exists: Bool in
    if exists {
        print("Player 42 exists.")
    } else {
        print("Player 42 does not exist.")
    }
}

:point_up: Note: the observations returned by the ValueObservation.trackingCount, trackingOne, and trackingAll methods already perform a similar filtering, based on raw database values.

ValueObservation.combine(…)

Sometimes you need to observe several requests at the same time. For example, you need to observe changes in both a team and its players.

When this happens, combine several observations together with the ValueObservation.combine(...) method:

// The two observed requests (the team and its players)
let teamRequest = Team.filter(key: 1)
let playersRequest = Player.filter(Column("teamId") == 1)

// Two observations
let teamObservation = ValueObservation.trackingOne(teamRequest)
let playersObservation = ValueObservation.trackingAll(playersRequest)

// The combined observation
let observation = ValueObservation.combine(teamObservation, playersObservation)

// Start tracking players and teams
let observer = observation.start(in: dbQueue) { (team: Team?, players: [Player]) in
    print("Team or players have changed.")
}

Combining observations provides the guarantee that notified values are consistent.

:point_up: Note: you can combine up to five observations together. Please submit a pull request if you need more.

point_up: Note: readers who are familiar with Reactive Programming will recognize the CombineLatest operator in the ValueObservation.combine method. The reactive operator does not care about data consistency, though: if you use a Reactive layer such as [RxGRDB], compose observations with ValueObservation.combine, not with the CombineLatest operator.

ValueObservation Error Handling

When you start an observation, you can provide an onError callback. This callback is called whenever an error happens when a fresh value is fetched after a database change. It is scheduled just like values (see ValueObservation.scheduling):

let observer = try observation.start(
    in: dbQueue,
    onError: { error in
        print("fresh value could not be fetched")
    },
    onChange: { value in
        print("fresh value: (value)")
    })

ValueObservation Options

Some behaviors of value observations can be configured:

ValueObservation.extent

The extent property lets you specify the duration of the observation.

The default extent is .observerLifetime: the observation stops when the observer returned by start is deallocated.

You can use the .databaseLifetime extent to specify that the observation lasts until the database connection is closed:

// No need to retain the observer returned by the start method:
var observation = ValueObservation...
observation.extent = .databaseLifetime
_ = observation.start(in: dbQueue) { newValue in ... }

:warning: Warning: Don’t use the .nextTransaction lifetime, because it produces unreliable results. A future version of GRDB will deprecate ValueObservation.extent, and provide a better API.

ValueObservation.scheduling

The scheduling property lets you control how fresh values are notified:

  • .mainQueue (the default): all values are notified on the main queue.

    If the observation starts on the main queue, an initial value is notified right upon subscription, synchronously:

    // On main queue
    let observer = ValueObservation
        .trackingAll(Player.all())
        .start(in: dbQueue) { players: [Player] in
            // On main queue
            print("fresh players: (players)")
        }
    // <- here "fresh players" is already printed.

    If the observation does not start on the main queue, an initial value is also notified on the main queue, but asynchronously:

    // Not on the main queue
    let observer = ValueObservation
        .trackingAll(Player.all())
        .start(in: dbQueue) { players: [Player] in
            // On main queue
            print("fresh players: (players)")
        }

    When the database changes, fresh values are asynchronously notified:

    // Eventually prints "fresh players" on the main queue
    try dbQueue.write { db in
        try Player(...).insert(db)
    }
  • .onQueue(_:startImmediately:): all values are asychronously notified on the specified queue.

    An initial value is fetched and notified if startImmediately is true.

    let customQueue = DispatchQueue(label: "customQueue")
    var observation = ValueObservation.trackingAll(Player.all())
    observation.scheduling = .onQueue(customQueue, startImmediately: true)
    let observer = try observation.start(in: dbQueue) { players: [Player] in
        // On customQueue
        print("fresh players: (players)")s
    }
  • unsafe(startImmediately:): values are not all notified on the same dispatch queue.

    If startImmediately is true, an initial value is notified right upon subscription, synchronously, on the dispatch queue which starts the observation.

    // On any queue
    var observation = ValueObservation.trackingAll(Player.all())
    observation.scheduling = .unsafe(startImmediately: true)
    let observer = try observation.start(in: dbQueue) { players: [Player] in
        print("fresh players: (players)")
    }
    // <- here "fresh players" is already printed.

    When the database changes, other values are notified on unspecified queues.

    :point_up: Note: this unsafe mode is intended for third-party libraries that provide their own scheduling engine.

ValueObservation.requiresWriteAccess

The requiresWriteAccess property is false by default. When true, a ValueObservation has a write access to the database, and its fetches are automatically wrapped in a savepoint:

var observation = ValueObservation.tracking(..., fetch: { db in
    // write access allowed
})
observation.requiresWriteAccess = true

When you use a database pool, don’t use this flag unless you really need it. Observations with write access are less efficient because they block all writes for the whole duration of a fetch.

Advanced: ValueObservation.tracking(_:reducer:)

The most low-level way to define a ValueObservation is to create one from an observed database region (see above), and a reducer that adopts the ValueReducer protocol (:fire: EXPERIMENTAL):

protocol ValueReducer {
    associatedtype Fetched
    associatedtype Value

    /// Fetches a database value
    func fetch(_ db: Database) throws -> Fetched

    /// Returns a notified value
    mutating func value(_ fetched: Fetched) -> Value?
}

The fetch method is called upon changes in the observed database region. It runs inside a protected dispatch queue and is guaranteed an immutable view of the last committed state of the database.

The value method transforms a fetched value into a notified value. It returns nil if the observer should not be notified. It runs inside a dispatch queue called the "reduce queue", which is not the main queue, and not a database queue.

The sample code below counts the number of times the player table is modified:

var count = 0
let reducer = AnyValueReducer(
    fetch: { _ in /* don't fetch anything */ },
    value: { _ -> Int? in
        defer { count += 1 }
        return count })
let observation = ValueObservation.tracking(Player.all(), reducer: { _ in reducer })
let observer = observation.start(in: dbQueue) { count: Int in
    print("Number of transactions that have modified players: (count)")
}
// Prints "Number of transactions that have modified players: 0"

try dbQueue.write { db in
    try Player(...).insert(db)
}
// Prints "Number of transactions that have modified players: 1"

DatabaseRegionObservation

DatabaseRegionObservation tracks changes in database requests, and notifies each impactful transaction.

No insertion, update, or deletion in the tracked tables is missed. This includes indirect changes triggered by foreign keys or SQL triggers.

DatabaseRegionObservation calls your application right after changes have been committed in the database, and before any other thread had any opportunity to perform further changes. This is a pretty strong guarantee, that most applications do not really need. Instead, most applications prefer to be notified with fresh values: make sure you check [ValueObservation] before using DatabaseRegionObservation.

DatabaseRegionObservation Usage

Define an observation by providing one or several requests to track:

// Track all players
let observation = DatabaseRegionObservation(tracking: Player.all())

Then start the observation from a database queue or pool:

let observer = observation.start(in: dbQueue) { db: Database in
    print("Players were changed")
}

And enjoy the changes notifications:

try dbQueue.write { db in
    try Player(name: "Arthur").insert(db)
}
// Prints "Players were changed"

By default, the observation lasts until the observer returned by the start method is deallocated. See DatabaseRegionObservation.extent for more details.

You can also feed DatabaseRegionObservation with [DatabaseRegion], or any type which conforms to the [DatabaseRegionConvertible] protocol. For example:

// Observe the full database
let observation = DatabaseRegionObservation(tracking: DatabaseRegion.fullDatabase)
let observer = observation.start(in: dbQueue) { db: Database in
    print("Database was changed")
}

DatabaseRegionObservation Use Cases

There are very few use cases for DatabaseRegionObservation.

For example:

  • One needs to write in the database after an impactful transaction.

  • One needs to synchronize the content of the database file with some external resources, like other files, or system sensors like CLRegion monitoring.

  • On iOS, one needs to process a database transaction before the operating system had any opportunity to put the application in the suspended state.

  • One want to build a database snapshot with a guaranteed snapshot content.

Outside of those use cases, it is much likely wrong to use a DatabaseRegionObservation. Please check other Database Observation options.

DatabaseRegionObservation.extent

The extent property lets you specify the duration of the observation. See Observation Extent for more details:

// This observation lasts until the database connection is closed
var observation = DatabaseRegionObservation...
observation.extent = .databaseLifetime
_ = observation.start(in: dbQueue) { db in ... }

The default extent is .observerLifetime: the observation stops when the observer returned by start is deallocated.

Regardless of the extent of an observation, you can always stop observation with the remove(transactionObserver:) method:

// Start
let observer = observation.start(in: dbQueue) { db in ... }

// Stop
dbQueue.remove(transactionObserver: observer)

FetchedRecordsController

FetchedRecordsController tracks changes in the results of a request, feeds table views and collection views, and animates cells when the results of the request change.

It looks and behaves very much like Core Data’s NSFetchedResultsController.

Given a fetch request, and a type that adopts the [FetchableRecord] protocol, such as a subclass of the Record class, a FetchedRecordsController is able to track changes in the results of the fetch request, notify of those changes, and return the results of the request in a form that is suitable for a table view or a collection view, with one cell per fetched record.

:point_up: Note: when you don’t need to animate a table or a collection view, use [ValueObservation] or [RxGRDB] instead.

bulb: Tip: see the Demo Application for a sample app that uses FetchedRecordsController.

Creating the Fetched Records Controller

When you initialize a fetched records controller, you provide the following mandatory information:

  • A database connection
  • The type of the fetched records. It must be a type that adopts the [FetchableRecord] protocol, such as a subclass of the Record class
  • A fetch request
class Player : Record { ... }
let dbQueue = DatabaseQueue(...)    // or DatabasePool

// Using a Request from the Query Interface:
let controller = FetchedRecordsController(
    dbQueue,
    request: Player.order(Column("name")))

// Using SQL, and eventual arguments:
let controller = FetchedRecordsController<Player>(
    dbQueue,
    sql: "SELECT * FROM player ORDER BY name WHERE countryCode = ?",
    arguments: ["FR"])

The fetch request can involve several database tables. The fetched records controller will only track changes in the columns and tables used by the fetch request.

let controller = FetchedRecordsController<Author>(
    dbQueue,
    sql: """
        SELECT author.name, COUNT(book.id) AS bookCount
        FROM author
        LEFT JOIN book ON book.authorId = author.id
        GROUP BY author.id
        ORDER BY author.name
        """)

After creating an instance, you invoke performFetch() to actually execute
the fetch.

try controller.performFetch()

Responding to Changes

In general, FetchedRecordsController is designed to respond to changes at the database layer, by notifying when database rows change location or values.

Changes are not reflected until they are applied in the database by a successful transaction:

// One transaction
try dbQueue.write { db in         // or dbPool.write
    try player1.insert(db)
    try player2.insert(db)
}

// One transaction
try dbQueue.inTransaction { db in // or dbPool.writeInTransaction
    try player1.insert(db)
    try player2.insert(db)
    return .commit
}

// Two transactions
try dbQueue.inDatabase { db in    // or dbPool.writeWithoutTransaction
    try player1.insert(db)
    try player2.insert(db)
}

When you apply several changes to the database, you should group them in a single explicit transaction. The controller will then notify of all changes together.

The Changes Notifications

An instance of FetchedRecordsController notifies that the controller’s fetched records have been changed by the mean of callbacks:

let controller = try FetchedRecordsController(...)

controller.trackChanges(
    // controller's records are about to change:
    willChange: { controller in ... },

    // notification of individual record changes:
    onChange: { (controller, record, change) in ... },

    // controller's records have changed:
    didChange: { controller in ... })

try controller.performFetch()

See Implementing Table View Updates for more detail on table view updates.

All callbacks are optional. When you only need to grab the latest results, you can omit the didChange argument name:

controller.trackChanges { controller in
    let newPlayers = controller.fetchedRecords // [Player]
}

:warning: Warning: notification of individual record changes (the onChange callback) has FetchedRecordsController use a diffing algorithm that has a high complexity, a high memory consumption, and is thus not suited for large result sets. One hundred rows is probably OK, but one thousand is probably not. If your application experiences problems with large lists, see Issue 263 for more information.

Callbacks have the fetched record controller itself as an argument: use it in order to avoid memory leaks:

// BAD: memory leak
controller.trackChanges { _ in
    let newPlayers = controller.fetchedRecords
}

// GOOD
controller.trackChanges { controller in
    let newPlayers = controller.fetchedRecords
}

Callbacks are invoked asynchronously. See FetchedRecordsController Concurrency for more information.

Values fetched from inside callbacks may be inconsistent with the controller’s records. This is because after database has changed, and before the controller had the opportunity to invoke callbacks in the main thread, other database changes can happen.

To avoid inconsistencies, provide a fetchAlongside argument to the trackChanges method, as below:

controller.trackChanges(
    fetchAlongside: { db in
        // Fetch any extra value, for example the number of fetched records:
        return try Player.fetchCount(db)
    },
    didChange: { (controller, count) in
        // The extra value is the second argument.
        let recordsCount = controller.fetchedRecords.count
        assert(count == recordsCount) // guaranteed
    })

Whenever the fetched records controller can not look for changes after a transaction has potentially modified the tracked request, an error handler is called. The request observation is not stopped, though: future transactions may successfully be handled, and the notified changes will then be based on the last successful fetch.

controller.trackErrors { (controller, error) in
    print("Missed a transaction because (error)")
}

Modifying the Fetch Request

You can change a fetched records controller’s fetch request or SQL query.

controller.setRequest(Player.order(Column("name")))
controller.setRequest(sql: "SELECT ...", arguments: ...)

The notification callbacks are notified of eventual changes if the new request fetches a different set of records.

:point_up: Note: This behavior differs from Core Data’s NSFetchedResultsController, which does not notify of record changes when the fetch request is replaced.

Change callbacks are invoked asynchronously. This means that modifying the request from the main thread does not immediately triggers callbacks. When you need to take immediate action, force the controller to refresh immediately with its performFetch method. In this case, changes callbacks are not called:

// Change request on the main thread:
controller.setRequest(Player.order(Column("name")))
// Here callbacks have not been called yet.
// You can cancel them, and refresh records immediately:
try controller.performFetch()

Table and Collection Views

FetchedRecordsController let you feed table and collection views, and keep them up-to-date with the database content.

For nice animated updates, a fetched records controller needs to recognize identical records between two different result sets. When records adopt the [TableRecord] protocol, they are automatically compared according to their primary key:

class Player : TableRecord { ... }
let controller = FetchedRecordsController(
    dbQueue,
    request: Player.all())

For other types, the fetched records controller needs you to be more explicit:

let controller = FetchedRecordsController(
    dbQueue,
    request: ...,
    isSameRecord: { (player1, player2) in player1.id == player2.id })

Implementing the Table View Datasource Methods

The table view data source asks the fetched records controller to provide relevant information:

func numberOfSections(in tableView: UITableView) -> Int {
    return fetchedRecordsController.sections.count
}

func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
    return fetchedRecordsController.sections[section].numberOfRecords
}

func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
    let cell = ...
    let record = fetchedRecordsController.record(at: indexPath)
    // Configure the cell
    return cell
}

:point_up: Note: In its current state, FetchedRecordsController does not support grouping table view rows into custom sections: it generates a unique section.

Implementing Table View Updates

When changes in the fetched records should reload the whole table view, you can simply tell so:

controller.trackChanges { [unowned self] _ in
    self.tableView.reloadData()
}

Yet, FetchedRecordsController can notify that the controller’s fetched records have been changed due to some add, remove, move, or update operations, and help applying animated changes to a UITableView.

Typical Table View Updates

For animated table view updates, use the willChange and didChange callbacks to bracket events provided by the fetched records controller, as illustrated in the following example:

// Assume self has a tableView property, and a cell configuration
// method named configure(_:at:).

controller.trackChanges(
    // controller's records are about to change:
    willChange: { [unowned self] _ in
        self.tableView.beginUpdates()
    },

    // notification of individual record changes:
    onChange: { [unowned self] (controller, record, change) in
        switch change {
        case .insertion(let indexPath):
            self.tableView.insertRows(at: [indexPath], with: .fade)

        case .deletion(let indexPath):
            self.tableView.deleteRows(at: [indexPath], with: .fade)

        case .update(let indexPath, _):
            if let cell = self.tableView.cellForRow(at: indexPath) {
                self.configure(cell, at: indexPath)
            }

        case .move(let indexPath, let newIndexPath, _):
            self.tableView.deleteRows(at: [indexPath], with: .fade)
            self.tableView.insertRows(at: [newIndexPath], with: .fade)

            // // Alternate technique which actually moves cells around:
            // let cell = self.tableView.cellForRow(at: indexPath)
            // self.tableView.moveRow(at: indexPath, to: newIndexPath)
            // if let cell = cell {
            //     self.configure(cell, at: newIndexPath)
            // }
        }
    },

    // controller's records have changed:
    didChange: { [unowned self] _ in
        self.tableView.endUpdates()
    })
:warning: Warning: notification of individual record changes (the onChange callback) has FetchedRecordsController use a diffing algorithm that has a high complexity, a high memory consumption, and is thus not suited for large result sets. One hundred rows is probably OK, but one thousand is probably not. If your application experiences problems with large lists, see Issue 263 for more information.

point_up: Note: our sample code above uses unowned references to the table view controller. This is a safe pattern as long as the table view controller owns the fetched records controller, and is deallocated from the main thread (this is usually the case). In other situations, prefer weak references.

bulb: Tip: see the Demo Application for a sample app that uses FetchedRecordsController to animate a table view.

FetchedRecordsController Concurrency

A fetched records controller can not be used from any thread.

When the database itself can be read and modified from any thread, fetched records controllers must be used from the main thread. Record changes are also notified on the main thread.

Change callbacks are invoked asynchronously. This means that changes made from the main thread are not immediately notified. When you need to take immediate action, force the controller to refresh immediately with its performFetch method. In this case, changes callbacks are not called:

// Change database on the main thread:
try dbQueue.write { db in
    try Player(...).insert(db)
}
// Here callbacks have not been called yet.
// You can cancel them, and refresh records immediately:
try controller.performFetch()

:point_up: Note: when the main thread does not fit your needs, give a serial dispatch queue to the controller initializer: the controller must then be used from this queue, and record changes are notified on this queue as well.

let queue = DispatchQueue()
queue.async {
    let controller = try FetchedRecordsController(..., queue: queue)
    controller.trackChanges { /* in queue */ }
    try controller.performFetch()
}

TransactionObserver Protocol

The TransactionObserver protocol lets you observe individual database changes and transactions:

protocol TransactionObserver : class {
    /// Notifies a database change:
    /// - event.kind (insert, update, or delete)
    /// - event.tableName
    /// - event.rowID
    ///
    /// For performance reasons, the event is only valid for the duration of
    /// this method call. If you need to keep it longer, store a copy:
    /// event.copy().
    func databaseDidChange(with event: DatabaseEvent)

    /// Filters the database changes that should be notified to the
    /// `databaseDidChange(with:)` method.
    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool

    /// An opportunity to rollback pending changes by throwing an error.
    func databaseWillCommit() throws

    /// Database changes have been committed.
    func databaseDidCommit(_ db: Database)

    /// Database changes have been rollbacked.
    func databaseDidRollback(_ db: Database)
}

Activate a Transaction Observer

To activate a transaction observer, add it to the database queue or pool:

let observer = MyObserver()
dbQueue.add(transactionObserver: observer)

By default, database holds weak references to its transaction observers: they are not retained, and stop getting notifications after they are deallocated. See Observation Extent for more options.

Database Changes And Transactions

A transaction observer is notified of all database changes: inserts, updates and deletes. This includes indirect changes triggered by ON DELETE and ON UPDATE actions associated to foreign keys, and SQL triggers.

:point_up: Note: the changes that are not notified are changes to internal system tables (such as sqlite_master), changes to WITHOUT ROWID tables, and the deletion of duplicate rows triggered by ON CONFLICT REPLACE clauses (this last exception might change in a future release of SQLite).

Notified changes are not actually written to disk until the transaction commits, and the databaseDidCommit callback is called. On the other side, databaseDidRollback confirms their invalidation:

try dbQueue.write { db in
    try db.execute("INSERT ...") // 1. didChange
    try db.execute("UPDATE ...") // 2. didChange
}                                // 3. willCommit, 4. didCommit

try dbQueue.inTransaction { db in
    try db.execute("INSERT ...") // 1. didChange
    try db.execute("UPDATE ...") // 2. didChange
    return .rollback             // 3. didRollback
}

try dbQueue.write { db in
    try db.execute("INSERT ...") // 1. didChange
    throw SomeError()
}                                // 2. didRollback

Database statements that are executed outside of any transaction do not drop off the radar:

try dbQueue.inDatabase { db in
    try db.execute("INSERT ...") // 1. didChange, 2. willCommit, 3. didCommit
    try db.execute("UPDATE ...") // 4. didChange, 5. willCommit, 6. didCommit
}

Changes that are on hold because of a savepoint are only notified after the savepoint has been released. This makes sure that notified events are only events that have an opportunity to be committed:

try dbQueue.inTransaction { db in
    try db.execute("INSERT ...")            // 1. didChange

    try db.execute("SAVEPOINT foo")
    try db.execute("UPDATE ...")            // delayed
    try db.execute("UPDATE ...")            // delayed
    try db.execute("RELEASE SAVEPOINT foo") // 2. didChange, 3. didChange

    try db.execute("SAVEPOINT foo")
    try db.execute("UPDATE ...")            // not notified
    try db.execute("ROLLBACK TO SAVEPOINT foo")

    return .commit                          // 4. willCommit, 5. didCommit
}

Eventual errors thrown from databaseWillCommit are exposed to the application code:

do {
    try dbQueue.inTransaction { db in
        ...
        return .commit           // 1. willCommit (throws), 2. didRollback
    }
} catch {
    // 3. The error thrown by the transaction observer.
}
:point_up: Note: all callbacks are called in a protected dispatch queue, and serialized with all database updates.

point_up: Note: the databaseDidChange(with:) and databaseWillCommit() callbacks must not touch the SQLite database. This limitation does not apply to databaseDidCommit and databaseDidRollback which can use their database argument.

[DatabaseRegionObservation], [ValueObservation], [FetchedRecordsController], and [RxGRDB] are based on the TransactionObserver protocol.

See also TableChangeObserver.swift, which shows a transaction observer that notifies of modified database tables with NSNotificationCenter.

Filtering Database Events

Transaction observers can avoid being notified of database changes they are not interested in.

The filtering happens in the observes(eventsOfKind:) method, which tells whether the observer wants notification of specific kinds of changes, or not. For example, here is how an observer can focus on the changes that happen on the "player" database table:

class PlayerObserver: TransactionObserver {
    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
        // Only observe changes to the "player" table.
        return eventKind.tableName == "player"
    }

    func databaseDidChange(with event: DatabaseEvent) {
        // This method is only called for changes that happen to
        // the "player" table.
    }
}

Generally speaking, the observes(eventsOfKind:) method can distinguish insertions from deletions and updates, and is also able to inspect the columns that are about to be changed:

class PlayerScoreObserver: TransactionObserver {
    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
        // Only observe changes to the "score" column of the "player" table.
        switch eventKind {
        case .insert(let tableName):
            return tableName == "player"
        case .delete(let tableName):
            return tableName == "player"
        case .update(let tableName, let columnNames):
            return tableName == "player" && columnNames.contains("score")
        }
    }
}

When the observes(eventsOfKind:) method returns false for all event kinds, the observer is still notified of commits and rollbacks:

class PureTransactionObserver: TransactionObserver {
    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
        // Ignore all individual changes
        return false
    }

    func databaseDidChange(with event: DatabaseEvent) { /* Never called */ }
    func databaseWillCommit() throws { /* Called before commit */ }
    func databaseDidRollback(_ db: Database) { /* Called on rollback */ }
    func databaseDidCommit(_ db: Database) { /* Called on commit */ }
}

For more information about event filtering, see [DatabaseRegion].

Observation Extent

You can specify how long an observer is notified of database changes and transactions.

The remove(transactionObserver:) method explicitly stops notifications, at any time:

// From a database queue or pool:
dbQueue.remove(transactionObserver: observer)

// From a database connection:
dbQueue.inDatabase { db in
    db.remove(transactionObserver: observer)
}

:point_up: Note: removing a transaction observer makes it sure it won’t be notified of any future transaction – there is no race condition. However, this does not stop eventual concurrent processing of previous transactions. For example, remove(transactionObserver:) is not a correct way to stop observers started by [ValueObservation]. In this case, the correct way is deallocating the observer.

Alternatively, use the extent parameter of the add(transactionObserver:extent:) method:

let observer = MyObserver()

// On a database queue or pool:
dbQueue.add(transactionObserver: observer) // default extent
dbQueue.add(transactionObserver: observer, extent: .observerLifetime)
dbQueue.add(transactionObserver: observer, extent: .nextTransaction)
dbQueue.add(transactionObserver: observer, extent: .databaseLifetime)

// On a database connection:
dbQueue.inDatabase { db in
    db.add(transactionObserver: ...)
}
  • The default extent is .observerLifetime: the database holds a weak reference to the observer, and the observation automatically ends when the observer is deallocated. Meanwhile, observer is notified of all changes and transactions.

  • .nextTransaction activates the observer until the current or next transaction completes. The database keeps a strong reference to the observer until its databaseDidCommit or databaseDidRollback method is eventually called. Hereafter the observer won’t get any further notification.

  • .databaseLifetime has the database retain and notify the observer until the database connection is closed.

Finally, an observer may ignore all database changes until the end of the current transaction:

class PlayerObserver: TransactionObserver {
    var playerTableWasModified = false

    func observes(eventsOfKind eventKind: DatabaseEventKind) -> Bool {
        return eventKind.tableName == "player"
    }

    func databaseDidChange(with event: DatabaseEvent) {
        playerTableWasModified = true

        // It is pointless to keep on tracking further changes:
        stopObservingDatabaseChangesUntilNextTransaction()
    }
}

After stopObservingDatabaseChangesUntilNextTransaction(), the databaseDidChange(with:) method will not be notified of any change for the remaining duration of the current transaction. This helps GRDB optimize database observation.

DatabaseRegion

DatabaseRegion is a type that helps observing changes in the results of a database request.

A request knows which database modifications can impact its results. It can communicate this information to transaction observers by the way of a DatabaseRegion.

DatabaseRegion fuels, for example, [ValueObservation and DatabaseRegionObservation].

A region notifies potential changes, not actual changes in the results of a request. A change is notified if and only if a statement has actually modified the tracked tables and columns by inserting, updating, or deleting a row.

For example, if you observe the region of Player.select(max(Column("score"))), then you’ll get be notified of all changes performed on the score column of the player table (updates, insertions and deletions), even if they do not modify the value of the maximum score. However, you will not get any notification for changes performed on other database tables, or updates to other columns of the player table.

Similarly, observing the region of Country.filter(key: "FR") will notify all changes that happen to the whole country table. That is because SQLite only notifies the numerical rowid of changed rows, and we can’t check if it is the row "FR" that has been changed, or another. This limitation does not apply to tables whose primary key is the rowid: Player.filter(key: 42) will only notify of changes performed on the row with id 42.

For more details, see the reference.

The DatabaseRegionConvertible Protocol

DatabaseRegionConvertible is a protocol for all types that can turn into a [DatabaseRegion]:

protocol DatabaseRegionConvertible {
    func databaseRegion(_ db: Database) throws -> DatabaseRegion
}

All requests adopt this protocol, and this allows them to be observed with [DatabaseRegionObservation] and [ValueObservation].

Use this protocol when you want to encapsulate your complex requests in a dedicated type, and still profit from observation APIs. See DatabaseRegionConvertible Observation for more information.

Support for SQLite Pre-Update Hooks

A custom SQLite build can activate SQLite "preupdate hooks". In this case, TransactionObserverType gets an extra callback which lets you observe individual column values in the rows modified by a transaction:

protocol TransactionObserverType : class {
    #if SQLITE_ENABLE_PREUPDATE_HOOK
    /// Notifies before a database change (insert, update, or delete)
    /// with change information (initial / final values for the row's
    /// columns).
    ///
    /// The event is only valid for the duration of this method call. If you
    /// need to keep it longer, store a copy: event.copy().
    func databaseWillChange(with event: DatabasePreUpdateEvent)
    #endif
}

Encryption

GRDB can encrypt your database with SQLCipher v3.4.2.

You can use CocoaPods (version 1.2 or higher), and specify in your Podfile:

use_frameworks!
pod 'GRDBCipher'

Alternatively, perform a manual installation of GRDB and SQLCipher:

  1. Clone the GRDB git repository, checkout the latest tagged version, and download SQLCipher sources:

    cd [GRDB directory]
    git checkout v3.6.1
    git submodule update --init SQLCipher/src
  2. Embed the GRDBCipher.xcodeproj project in your own project.

  3. Add the GRDBCipherOSX or GRDBCipheriOS target in the Target Dependencies section of the Build Phases tab of your application target.

  4. Add the GRDBCipher.framework from the targetted platform to the Embedded Binaries section of the General tab of your target.

You create and open an encrypted database by providing a passphrase to your database connection:

import GRDBCipher

var configuration = Configuration()
configuration.passphrase = "secret"
let dbQueue = try DatabaseQueue(path: "...", configuration: configuration)

You can change the passphrase of an already encrypted database:

try dbQueue.change(passphrase: "newSecret")

Providing a passphrase won’t encrypt a clear-text database that already exists, though. SQLCipher can’t do that, and you will get an error instead: SQLite error 26: file is encrypted or is not a database.

To encrypt an existing clear-text database, create a new and empty encrypted database, and copy the content of the clear-text database in it. The technique to do that is documented by SQLCipher. With GRDB, it gives:

// The clear-text database
let clearDBQueue = try DatabaseQueue(path: "/path/to/clear.db")

// The encrypted database, at some distinct location:
var configuration = Configuration()
configuration.passphrase = "secret"
let encryptedDBQueue = try DatabaseQueue(path: "/path/to/encrypted.db", configuration: config)

try clearDBQueue.inDatabase { db in
    try db.execute("ATTACH DATABASE ? AS encrypted KEY ?", arguments: [encryptedDBQueue.path, "secret"])
    try db.execute("SELECT sqlcipher_export('encrypted')")
    try db.execute("DETACH DATABASE encrypted")
}

// Now the copy is done, and the clear-text database can be deleted.

Backup

You can backup (copy) a database into another.

Backups can for example help you copying an in-memory database to and from a database file when you implement NSDocument subclasses.

let source: DatabaseQueue = ...      // or DatabasePool
let destination: DatabaseQueue = ... // or DatabasePool
try source.backup(to: destination)

The backup method blocks the current thread until the destination database contains the same contents as the source database.

When the source is a database pool, concurrent writes can happen during the backup. Those writes may, or may not, be reflected in the backup, but they won’t trigger any error.

Avoiding SQL Injection

SQL injection is a technique that lets an attacker nuke your database.

XKCD: Exploits of a Mom

https://xkcd.com/327/

Here is an example of code that is vulnerable to SQL injection:

// BAD BAD BAD
let id = 1
let name = textField.text
try dbQueue.write { db in
    try db.execute("UPDATE students SET name = '(name)' WHERE id = (id)")
}

If the user enters a funny string like Robert'; DROP TABLE students; --, SQLite will see the following SQL, and drop your database table instead of updating a name as intended:

UPDATE students SET name = 'Robert';
DROP TABLE students;
--' WHERE id = 1

To avoid those problems, never embed raw values in your SQL queries. The only correct technique is to provide arguments to your raw SQL queries:

let name = textField.text
try dbQueue.write { db in
    // Good
    try db.execute(
        "UPDATE students SET name = ? WHERE id = ?",
        arguments: [name, id])

    // Just as good
    try db.execute(
        "UPDATE students SET name = :name WHERE id = :id",
        arguments: ["name": name, "id": id])
}

When you use records and the query interface, GRDB always prevents SQL injection for you:

let id = 1
let name = textField.text
try dbQueue.write { db in
    if var student = try Student.fetchOne(db, key: id) {
        student.name = name
        try student.update(db)
    }
}

Error Handling

GRDB can throw DatabaseError, PersistenceError, or crash your program with a fatal error.

Considering that a local database is not some JSON loaded from a remote server, GRDB focuses on trusted databases. Dealing with untrusted databases requires extra care.

DatabaseError

DatabaseError are thrown on SQLite errors:

do {
    try db.execute(
        "INSERT INTO pet (masterId, name) VALUES (?, ?)",
        arguments: [1, "Bobby"])
} catch let error as DatabaseError {
    // The SQLite error code: 19 (SQLITE_CONSTRAINT)
    error.resultCode

    // The extended error code: 787 (SQLITE_CONSTRAINT_FOREIGNKEY)
    error.extendedResultCode

    // The eventual SQLite message: FOREIGN KEY constraint failed
    error.message

    // The eventual erroneous SQL query
    // "INSERT INTO pet (masterId, name) VALUES (?, ?)"
    error.sql

    // Full error description:
    // "SQLite error 19 with statement `INSERT INTO pet (masterId, name)
    //  VALUES (?, ?)` arguments [1, "Bobby"]: FOREIGN KEY constraint failed""
    error.description
}

SQLite uses codes to distinguish between various errors:

do {
    try ...
} catch let error as DatabaseError where error.extendedResultCode == .SQLITE_CONSTRAINT_FOREIGNKEY {
    // foreign key constraint error
} catch let error as DatabaseError where error.resultCode == .SQLITE_CONSTRAINT {
    // any other constraint error
} catch let error as DatabaseError {
    // any other database error
}

In the example above, error.extendedResultCode is a precise extended result code, and error.resultCode is a less precise primary result code. Extended result codes are refinements of primary result codes, as SQLITE_CONSTRAINT_FOREIGNKEY is to SQLITE_CONSTRAINT, for example. See SQLite result codes for more information.

As a convenience, extended result codes match their primary result code in a switch statement:

do {
    try ...
} catch let error as DatabaseError {
    switch error.extendedResultCode {
    case ResultCode.SQLITE_CONSTRAINT_FOREIGNKEY:
        // foreign key constraint error
    case ResultCode.SQLITE_CONSTRAINT:
        // any other constraint error
    default:
        // any other database error
    }
}

:warning: Warning: SQLite has progressively introduced extended result codes accross its versions. For example, SQLITE_CONSTRAINT_FOREIGNKEY wasn’t introduced yet on iOS 8.1. The SQLite release notes are unfortunately not quite clear about that: write your handling of extended result codes with care.

PersistenceError

PersistenceError is thrown by the [PersistableRecord] protocol, in a single case: when the update method could not find any row to update:

do {
    try player.update(db)
} catch PersistenceError.recordNotFound {
    // There was nothing to update
}

Fatal Errors

Fatal errors notify that the program, or the database, has to be changed.

They uncover programmer errors, false assumptions, and prevent misuses. Here are a few examples:

  • The code asks for a non-optional value, when the database contains NULL:

    // fatal error: could not convert NULL to String.
    let name: String = row["name"]

    Solution: fix the contents of the database, use NOT NULL constraints, or load an optional:

    let name: String? = row["name"]
  • Conversion from database value to Swift type fails:

    // fatal error: could not convert "Mom’s birthday" to Date.
    let date: Date = row["date"]
    
    // fatal error: could not convert "" to URL.
    let url: URL = row["url"]

    Solution: fix the contents of the database, or use DatabaseValue to handle all possible cases:

    let dbValue: DatabaseValue = row["date"]
    if dbValue.isNull {
        // Handle NULL
    } else if let date = Date.fromDatabaseValue(dbValue) {
        // Handle valid date
    } else {
        // Handle invalid date
    }
  • The database can’t guarantee that the code does what it says:

    // fatal error: table player has no unique index on column email
    try Player.deleteOne(db, key: ["email": "[email protected]"])

    Solution: add a unique index to the player.email column, or use the deleteAll method to make it clear that you may delete more than one row:

    try Player.filter(Column("email") == "[email protected]").deleteAll(db)
  • Database connections are not reentrant:

    // fatal error: Database methods are not reentrant.
    dbQueue.write { db in
        dbQueue.write { db in
            ...
        }
    }

    Solution: avoid reentrancy, and instead pass a database connection along.

How to Deal with Untrusted Inputs

Let’s consider the code below:

let sql = "SELECT ..."

// Some untrusted arguments for the query
let arguments: [String: Any] = ...
let rows = try Row.fetchCursor(db, sql, arguments: StatementArguments(arguments))

while let row = try rows.next() {
    // Some untrusted database value:
    let date: Date? = row[0]
}

It has two opportunities to throw fatal errors:

  • Untrusted arguments: The dictionary may contain values that do not conform to the DatabaseValueConvertible protocol, or may miss keys required by the statement.
  • Untrusted database content: The row may contain a non-null value that can’t be turned into a date.

In such a situation, you can still avoid fatal errors by exposing and handling each failure point, one level down in the GRDB API:

// Untrusted arguments
if let arguments = StatementArguments(arguments) {
    let statement = try db.makeSelectStatement(sql)
    try statement.validate(arguments: arguments)
    statement.unsafeSetArguments(arguments)

    var cursor = try Row.fetchCursor(statement)
    while let row = try iterator.next() {
        // Untrusted database content
        let dbValue: DatabaseValue = row[0]
        if dbValue.isNull {
            // Handle NULL
        if let date = Date.fromDatabaseValue(dbValue) {
            // Handle valid date
        } else {
            // Handle invalid date
        }
    }
}

See prepared statements and DatabaseValue for more information.

Error Log

SQLite can be configured to invoke a callback function containing an error code and a terse error message whenever anomalies occur.

This global error callback must be configured early in the lifetime of your application:

Database.logError = { (resultCode, message) in
    NSLog("%@", "SQLite error (resultCode): (message)")
}

:warning: Warning: Database.logError must be set before any database connection is opened. This includes the connections that your application opens with GRDB, but also connections opened by other tools, such as third-party libraries. Setting it after a connection has been opened is an SQLite misuse, and has no effect.

See The Error And Warning Log for more information.

Unicode

SQLite lets you store unicode strings in the database.

However, SQLite does not provide any unicode-aware string transformations or comparisons.

Unicode functions

The UPPER and LOWER built-in SQLite functions are not unicode-aware:

// "JéRôME"
try String.fetchOne(db, "SELECT UPPER('Jérôme')")

GRDB extends SQLite with SQL functions that call the Swift built-in string functions capitalized, lowercased, uppercased, localizedCapitalized, localizedLowercased and localizedUppercased:

// "JÉRÔME"
let uppercased = DatabaseFunction.uppercase
try String.fetchOne(db, "SELECT (uppercased.name)('Jérôme')")

Those unicode-aware string functions are also readily available in the query interface:

Player.select(nameColumn.uppercased)

String Comparison

SQLite compares strings in many occasions: when you sort rows according to a string column, or when you use a comparison operator such as = and <=.

The comparison result comes from a collating function, or collation. SQLite comes with three built-in collations that do not support Unicode: binary, nocase, and rtrim.

GRDB comes with five extra collations that leverage unicode-aware comparisons based on the standard Swift String comparison functions and operators:

  • unicodeCompare (uses the built-in <= and == Swift operators)
  • caseInsensitiveCompare
  • localizedCaseInsensitiveCompare
  • localizedCompare
  • localizedStandardCompare

A collation can be applied to a table column. All comparisons involving this column will then automatically trigger the comparison function:

try db.create(table: "player") { t in
    // Guarantees case-insensitive email unicity
    t.column("email", .text).unique().collate(.nocase)

    // Sort names in a localized case insensitive way
    t.column("name", .text).collate(.localizedCaseInsensitiveCompare)
}

// Players are sorted in a localized case insensitive way:
let players = try Player.order(nameColumn).fetchAll(db)

:warning: Warning: SQLite requires host applications to provide the definition of any collation other than binary, nocase and rtrim. When a database file has to be shared or migrated to another SQLite library of platform (such as the Android version of your application), make sure you provide a compatible collation.

If you can’t or don’t want to define the comparison behavior of a column (see warning above), you can still use an explicit collation in SQL requests and in the query interface:

let collation = DatabaseCollation.localizedCaseInsensitiveCompare
let players = try Player.fetchAll(db,
    "SELECT * FROM player ORDER BY name COLLATE (collation.name))")
let players = try Player.order(nameColumn.collating(collation)).fetchAll(db)

You can also define your own collations:

let collation = DatabaseCollation("customCollation") { (lhs, rhs) -> NSComparisonResult in
    // return the comparison of lhs and rhs strings.
}
dbQueue.add(collation: collation) // Or dbPool.add(collation: ...)

Memory Management

Both SQLite and GRDB use non-essential memory that help them perform better.

You can reclaim this memory with the releaseMemory method:

// Release as much memory as possible.
dbQueue.releaseMemory()
dbPool.releaseMemory()

This method blocks the current thread until all current database accesses are completed, and the memory collected.

Memory Management on iOS

The iOS operating system likes applications that do not consume much memory.

Database queues and pools can call the releaseMemory method for you, when application receives memory warnings, and when application enters background: call the setupMemoryManagement method after creating the queue or pool instance:

let dbQueue = try DatabaseQueue(...)
dbQueue.setupMemoryManagement(in: UIApplication.shared)

Data Protection

Data Protection lets you protect files so that they are encrypted and unavailable until the device is unlocked.

Data protection can be enabled globally for all files created by an application.

You can also explicitly protect a database, by configuring its enclosing directory. This will not only protect the database file, but also all temporary files created by SQLite (including the persistent .shm and .wal files created by database pools).

For example, to explicitly use complete protection:

// Paths
let fileManager = FileManager.default
let directoryURL = try fileManager
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("database", isDirectory: true)
let databaseURL = directoryURL.appendingPathComponent("db.sqlite")

// Create directory if needed
var isDirectory: ObjCBool = false
if !fileManager.fileExists(atPath: directoryURL.path, isDirectory: &isDirectory) {
    try fileManager.createDirectory(atPath: directoryURL.path, withIntermediateDirectories: false)
} else if !isDirectory.boolValue {
    throw NSError(domain: NSCocoaErrorDomain, code: NSFileWriteFileExistsError, userInfo: nil)
}

// Enable data protection
try fileManager.setAttributes([.protectionKey : FileProtectionType.complete], ofItemAtPath: directoryURL.path)

// Open database
let dbQueue = try DatabaseQueue(path: databaseURL.path)

When a database is protected, an application that runs in the background on a locked device won’t be able to read or write from it. Instead, it will get DatabaseError with code SQLITE_IOERR (10) "disk I/O error", or SQLITE_AUTH (23) "not authorized".

You can catch those errors and wait for UIApplicationDelegate.applicationProtectedDataDidBecomeAvailable(_:) or UIApplicationProtectedDataDidBecomeAvailable notification in order to retry the failed database operation.

Concurrency

Guarantees and Rules

GRDB ships with three concurrency modes:

  • DatabaseQueue opens a single database connection, and serializes all database accesses.
  • DatabasePool manages a pool of several database connections, and allows concurrent reads and writes.
  • DatabaseSnapshot opens a single read-only database connection on an unchanging database content, and (currently) serializes all database accesses

All foster application safety: regardless of the concurrency mode you choose, GRDB provides you with the same guarantees, as long as you follow three rules.

  • :bowtie: Guarantee 1: writes are always serialized. At every moment, there is no more than a single thread that is writing into the database.

    Database writes always happen in a unique serial dispatch queue, named the writer protected dispatch queue.

  • :bowtie: Guarantee 2: reads are always isolated. This means that they are guaranteed an immutable view of the last committed state of the database, and that you can perform subsequent fetches without fearing eventual concurrent writes to mess with your application logic:

    try dbPool.read { db in // or dbQueue.read
        // Guaranteed to be equal
        let count1 = try Player.fetchCount(db)
        let count2 = try Player.fetchCount(db)
    }

    In database queues, reads happen in the same protected dispatch queue as writes: isolation is just a consequence of the serialization of database accesses

    Database pools and snapshots both use the "snapshot isolation" made possible by SQLite’s WAL mode (see Isolation In SQLite).

  • :bowtie: Guarantee 3: requests don’t fail, unless a database constraint violation, a programmer mistake, or a very low-level issue such as a disk error or an unreadable database file. GRDB grants correct use of SQLite, and particularly avoids locking errors and other SQLite misuses.

Those guarantees hold as long as you follow three rules:

  • :point_up: Rule 1: Have a unique instance of DatabaseQueue or DatabasePool connected to any database file.

    This means that opening a new connection each time you access the database is a bad idea. Do share a single connection instead.

    See the Demo Application for a sample app that sets up a single database queue that is available throughout the application.

    If there are several instances of database queues or pools that write in the same database, a multi-threaded application will eventually face "database is locked" errors. See Dealing with External Connections.

    // SAFE CONCURRENCY
    func fetchCurrentUser(_ db: Database) throws -> User? {
        return try User.fetchOne(db)
    }
    // dbQueue is a singleton defined somewhere in your app
    let user = try dbQueue.read { db in // or dbPool.read
        try fetchCurrentUser(db)
    }
    
    // UNSAFE CONCURRENCY
    // This method fails when some other thread is currently writing into
    // the database.
    func currentUser() throws -> User? {
        let dbQueue = try DatabaseQueue(...)
        return try dbQueue.read { db in
            try User.fetchOne(db)
        }
    }
    let user = try currentUser()
  • :point_up: Rule 2: Group related statements within a single call to a DatabaseQueue or DatabasePool database access method (or use snapshots).

    Database access methods isolate your groups of related statements against eventual database updates performed by other threads, and guarantee a consistent view of the database. This isolation is only guaranteed inside the closure argument of those methods. Two consecutive calls do not guarantee isolation:

    // SAFE CONCURRENCY
    try dbPool.read { db in  // or dbQueue.read
        // Guaranteed to be equal:
        let count1 = try Place.fetchCount(db)
        let count2 = try Place.fetchCount(db)
    }
    
    // UNSAFE CONCURRENCY
    // Those two values may be different because some other thread may have
    // modified the database between the two blocks:
    let count1 = try dbPool.read { db in try Place.fetchCount(db) }
    let count2 = try dbPool.read { db in try Place.fetchCount(db) }

    In the same vein, when you fetch values that depends on some database updates, group them:

    // SAFE CONCURRENCY
    try dbPool.write { db in
        // The count is guaranteed to be non-zero
        try Place(...).insert(db)
        let count = try Place.fetchCount(db)
    }
    
    // UNSAFE CONCURRENCY
    // The count may be zero because some other thread may have performed
    // a deletion between the two blocks:
    try dbPool.write { db in try Place(...).insert(db) }
    let count = try dbPool.read { db in try Place.fetchCount(db) }

    On that last example, see Advanced DatabasePool if you look after extra performance.

  • :point_up: Rule 3: When you perform several modifications of the database that temporarily put the database in an inconsistent state, make sure those modifications are grouped within a transaction.

    // SAFE CONCURRENCY
    try dbPool.write { db in               // or dbQueue.write
        try Credit(destinationAccout, amount).insert(db)
        try Debit(sourceAccount, amount).insert(db)
    }
    
    // SAFE CONCURRENCY
    try dbPool.writeInTransaction { db in  // or dbQueue.inTransaction
        try Credit(destinationAccout, amount).insert(db)
        try Debit(sourceAccount, amount).insert(db)
        return .commit
    }
    
    // UNSAFE CONCURRENCY
    try dbPool.writeWithoutTransaction { db in
        try Credit(destinationAccout, amount).insert(db)
        // <- Concurrent dbPool.read sees a partial db update here
        try Debit(sourceAccount, amount).insert(db)
    }

    Without transaction, DatabasePool.read { ... } may see the first statement, but not the second, and access a database where the balance of accounts is not zero. A highly bug-prone situation.

    So do use transactions in order to guarantee database consistency accross your application threads: that’s what they are made for.

Differences between Database Queues and Pools

Despite the common guarantees and rules shared by database queues and pools, those two database accessors don’t have the same behavior.

Database queues serialize all database accesses, reads, and writes. There is never more than one thread that uses the database. In the image below, we see how three threads can see the database as time passes:

DatabaseQueueScheduling

Database pools also serialize all writes. But they allow concurrent reads and writes, and isolate reads so that they don’t see changes performed by other threads. This gives a very different picture:

DatabasePoolScheduling

See how, with database pools, two reads can see different database states at the same time.

For more information about database pools, grab information about SQLite WAL mode and snapshot isolation. See Database Observation when you look after automatic notifications of database changes.

Advanced DatabasePool

Database pools are very concurrent, since all reads can run in parallel, and can even run during write operations. But writes are still serialized: at any given point in time, there is no more than a single thread that is writing into the database.

When your application modifies the database, and then reads some value that depends on those modifications, you may want to avoid locking the writer queue longer than necessary:

try dbPool.write { db in
    // Increment the number of players
    try Player(...).insert(db)

    // Read the number of players. The writer queue is still locked :-(
    let count = try Player.fetchCount(db)
}

A wrong solution is to chain a write then a read, as below. Don’t do that, because another thread may modify the database in between, and make the read unreliable:

// WRONG
try dbPool.write { db in
    // Increment the number of players
    try Player(...).insert(db)
}
// <- other threads can write in the database here
try dbPool.read { db in
    // Read some random value :-(
    let count = try Player.fetchCount(db)
}

The correct solution is the concurrentRead method, which must be called from within a write block, outside of any transaction.

concurrentRead returns a future value which you consume on any dispatch queue, with the wait() method:

// CORRECT
let futureCount: Future<Int> = try dbPool.writeWithoutTransaction { db in
    // increment the number of players
    try Player(...).insert(db)

    // <- not in a transaction here
    let futureCount = dbPool.concurrentRead { db
        return try Player.fetchCount(db)
    }
    return futureCount
}
// <- The writer queue has been unlocked :-)

// Wait for the player count
let count: Int = try futureCount.wait()

concurrentRead blocks until it can guarantee its closure argument an isolated access to the last committed state of the database. It then asynchronously executes the closure.

The closure can run concurrently with eventual updates performed after concurrentRead: those updates won’t be visible from within the closure. In the example below, the number of players is guaranteed to be non-zero, even though it is fetched concurrently with the player deletion:

try dbPool.writeWithoutTransaction { db in
    // Increment the number of players
    try Player(...).insert(db)

    let futureCount = dbPool.concurrentRead { db
        // Guaranteed to be non-zero
        return try Player.fetchCount(db)
    }

    try Player.deleteAll(db)
}

Transaction Observers can also use concurrentRead in their databaseDidCommit method in order to process database changes without blocking other threads that want to write into the database.

Database Snapshots

A database snapshot sees an unchanging database content, as it existed at the moment it was created.

"Unchanging" means that a snapshot never sees any database modifications during all its lifetime. And yet it doesn’t prevent database updates. This "magic" is made possible by SQLite’s WAL mode (see Isolation In SQLite).

You create snapshots from a database pool:

let snapshot = try dbPool.makeSnapshot()

You can create as many snapshots as you need, regardless of the maximum number of readers in the pool. A snapshot database connection is closed when the snapshot gets deallocated.

A snapshot can be used from any thread. Its read methods is synchronous, and blocks the current thread until your database statements are executed:

// Read values:
try snapshot.read { db in
    let players = try Player.fetchAll(db)
    let playerCount = try Player.fetchCount(db)
}

// Extract a value from the database:
let playerCount = try snapshot.read { db in
    try Player.fetchCount(db)
}

When you want to control the latest committed changes seen by a snapshot, create it from the pool’s writer protected dispatch queue, outside of any transaction:

let snapshot1 = try dbPool.writeWithoutTransaction { db -> DatabaseSnapshot in
    try db.inTransaction {
        // delete all players
        try Player.deleteAll()
        return .commit
    }

    // <- not in a transaction here
    return dbPool.makeSnapshot()
}
// <- Other threads may modify the database here
let snapshot2 = try dbPool.makeSnapshot()

try snapshot1.read { db in
    // Guaranteed to be zero
    try Player.fetchCount(db)
}

try snapshot2.read { db in
    // Could be anything
    try Player.fetchCount(db)
}

:point_up: Note: snapshots currently serialize all database accesses. In the future, snapshots may allow concurrent reads.

DatabaseWriter and DatabaseReader Protocols

Both DatabaseQueue and DatabasePool adopt the DatabaseReader and DatabaseWriter protocols. DatabaseSnapshot adopts DatabaseReader only.

These protocols provide a unified API that let you write generic code that targets all concurrency modes. They fuel, for example:

  • Migrations
  • [DatabaseRegionObservation]
  • [ValueObservation]
  • [FetchedRecordsController]
  • [RxGRDB]

Only five types adopt those protocols: DatabaseQueue, DatabasePool, DatabaseSnapshot, AnyDatabaseReader, and AnyDatabaseWriter. Expanding this set is not supported: any future GRDB release may break your custom writers and readers, without notice.

DatabaseReader and DatabaseWriter provide the smallest common guarantees: they don’t erase the differences between queues, pools, and snapshots. See for example Differences between Database Queues and Pools.

However, you can prevent some parts of your application from writing in the database by giving them a DatabaseReader:

// This class can read in the database, but can't write into it.
class MyReadOnlyComponent {
    let reader: DatabaseReader

    init(reader: DatabaseReader) {
        self.reader = reader
    }
}

let dbQueue: DatabaseQueue = ...
let component = MyReadOnlyComponent(reader: dbQueue)

:point_up: Note: DatabaseReader is not a secure way to prevent an application component from writing in the database, because write access is just a cast away:

if let dbQueue = reader as? DatabaseQueue {
    try dbQueue.write { ... }
}

Unsafe Concurrency APIs

Database queues, pools, snapshots, as well as their common protocols DatabaseReader and DatabaseWriter provide unsafe APIs. Unsafe APIs lift concurrency guarantees, and allow advanced yet unsafe patterns.

  • unsafeRead

    The unsafeRead method is synchronous, and blocks the current thread until your database statements are executed in a protected dispatch queue. GRDB does just the bare minimum to provide a database connection that can read.

    When used on a database pool, reads are no longer isolated:

    dbPool.unsafeRead { db in
        // Those two values may be different because some other thread
        // may have inserted or deleted a player between the two requests:
        let count1 = try Player.fetchCount(db)
        let count2 = try Player.fetchCount(db)
    }

    When used on a database queue, the closure argument is allowed to write in the database.

  • unsafeReentrantRead

    The unsafeReentrantRead behaves just as unsafeRead (see above), and allows reentrant calls:

    dbPool.read { db1 in
        // No "Database methods are not reentrant" fatal error:
        dbPool.unsafeReentrantRead { db2 in
            dbPool.unsafeReentrantRead { db3 in
                ...
            }
        }
    }

    Reentrant database accesses make it very easy to break the second safety rule, which says: "group related statements within a single call to a DatabaseQueue or DatabasePool database access method.". Using a reentrant method is pretty much likely the sign of a wrong application architecture that needs refactoring.

    There is a single valid use case for reentrant methods, which is when you are unable to control database access scheduling.

  • unsafeReentrantWrite

    The unsafeReentrantWrite method is synchronous, and blocks the current thread until your database statements are executed in a protected dispatch queue. Writes are serialized: eventual concurrent database updates are postponed until the block has executed.

    Reentrant calls are allowed:

    dbQueue.write { db1 in
        // No "Database methods are not reentrant" fatal error:
        dbQueue.unsafeReentrantWrite { db2 in
            dbQueue.unsafeReentrantWrite { db3 in
                ...
            }
        }
    }

    Reentrant database accesses make it very easy to break the second safety rule, which says: "group related statements within a single call to a DatabaseQueue or DatabasePool database access method.". Using a reentrant method is pretty much likely the sign of a wrong application architecture that needs refactoring.

    There is a single valid use case for reentrant methods, which is when you are unable to control database access scheduling.

Dealing with External Connections

The first rule of GRDB is:

  • Rule 1: Have a unique instance of DatabaseQueue or DatabasePool connected to any database file.

This means that dealing with external connections is not a focus of GRDB. Guarantees of GRDB may or may not hold as soon as some external connection modifies a database.

If you absolutely need multiple connections, then:

Performance

GRDB is a reasonably fast library, and can deliver quite efficient SQLite access. See Comparing the Performances of Swift SQLite libraries for an overview.

You’ll find below general advice when you do look after performance:

  • Focus
  • Know your platform
  • Use transactions
  • Don’t do useless work
  • Learn about SQL strengths and weaknesses
  • Avoid strings & dictionaries

Performance tip: focus

You don’t know which part of your program needs improvement until you have run a benchmarking tool.

Don’t make any assumption, avoid optimizing code too early, and use Instruments.

Performance tip: know your platform

If your application processes a huge JSON file and inserts thousands of rows in the database right from the main thread, it will quite likely become unresponsive, and provide a sub-quality user experience.

If not done yet, read the Concurrency Programming Guide and learn how to perform heavy computations without blocking your application.

Most GRBD APIs are synchronous. Spawning them into parallel queues is as easy as:

DispatchQueue.global().async { 
    dbQueue.write { db in
        // Perform database work
    }
    DispatchQueue.main.async { 
        // update your user interface
    }
}

Performance tip: use transactions

Performing multiple updates to the database is much faster when executed inside a transaction. This is because a transaction allows SQLite to postpone writing changes to disk until the final commit:

// Inefficient
try dbQueue.inDatabase { db in // or dbPool.writeWithoutTransaction
    for player in players {
        try player.insert(db)
    }
}

// Efficient
try dbQueue.write { db in      // or dbPool.write
    for player in players {
        try player.insert(db)
    }
}

// Efficient
try dbQueue.inTransaction { db in // or dbPool.writeInTransaction
    for player in players {
        try player.insert(db)
    }
    return .commit
}

Performance tip: don’t do useless work

Obviously, no code is faster than any code.

Don’t fetch columns you don’t use

// SELECT * FROM player
try Player.fetchAll(db)

// SELECT id, name FROM player
try Player.select(idColumn, nameColumn).fetchAll(db)

If your Player type can’t be built without other columns (it has non-optional properties for other columns), do define and use a different type.

See [Columns Selected by a Request] for more information.

Don’t fetch rows you don’t use

Use fetchOne when you need a single value, and otherwise limit your queries at the database level:

// Wrong way: this code may discard hundreds of useless database rows
let players = try Player.order(scoreColumn.desc).fetchAll(db)
let hallOfFame = players.prefix(5)

// Better way
let hallOfFame = try Player.order(scoreColumn.desc).limit(5).fetchAll(db)

Don’t copy values unless necessary

Particularly: the Array returned by the fetchAll method, and the cursor returned by fetchCursor aren’t the same:

fetchAll copies all values from the database into memory, when fetchCursor iterates database results as they are generated by SQLite, taking profit from SQLite efficiency.

You should only load arrays if you need to keep them for later use (such as iterating their contents in the main thread). Otherwise, use fetchCursor.

See fetching methods for more information about fetchAll and fetchCursor. See also the Row.dataNoCopy method.

Don’t update rows unless necessary

An UPDATE statement is costly: SQLite has to look for the updated row, update values, and write changes to disk.

When the overwritten values are the same as the existing ones, it’s thus better to avoid performing the UPDATE statement:.

if player.hasDatabaseChanges {
    try player.update(db)
}

See [Record Comparison] for more information.

Performance tip: learn about SQL strengths and weaknesses

Consider a simple use case: your store application has to display a list of authors with the number of available books:

  • J. M. Coetzee (6)
  • Herman Melville (1)
  • Alice Munro (3)
  • Kim Stanley Robinson (7)
  • Oliver Sacks (4)

The following code is inefficient. It is an example of the N+1 problem, because it performs one query to load the authors, and then N queries, as many as there are authors. This turns very inefficient as the number of authors grows:

// SELECT * FROM author
let authors = try Author.fetchAll(db)
for author in authors {
    // SELECT COUNT(*) FROM book WHERE authorId = ...
    author.bookCount = try Book.filter(authorIdColumn == author.id).fetchCount(db)
}

Instead, perform a single query:

let sql = """
    SELECT author.*, COUNT(book.id) AS bookCount
    FROM author
    LEFT JOIN book ON book.authorId = author.id
    GROUP BY author.id
    """
let authors = try Author.fetchAll(db, sql)

In the example above, consider extending your Author with an extra bookCount property, or define and use a different type.

Generally, define indexes on your database tables, and use SQLite’s efficient query planning:

Performance tip: avoid strings & dictionaries

The String and Dictionary Swift types are better avoided when you look for the best performance.

Now GRDB records, for your convenience, do use strings and dictionaries:

class Player : Record {
    var id: Int64?
    var name: String
    var email: String

    required init(_ row: Row) {
        id = row["id"]       // String
        name = row["name"]   // String
        email = row["email"] // String
        super.init()
    }

    override func encode(to container: inout PersistenceContainer) {
        container["id"] = id              // String
        container["name"] = name          // String
        container["email"] = email        // String
    }
}

When convenience hurts performance, you can still use records, but you have better avoiding their string and dictionary-based methods.

For example, when fetching values, prefer loading columns by index:

// Strings & dictionaries
let players = try Player.fetchAll(db)

// Column indexes
// SELECT id, name, email FROM player
let request = Player.select(idColumn, nameColumn, emailColumn)
let rows = try Row.fetchCursor(db, request)
while let row = try rows.next() {
    let id: Int64 = row[0]
    let name: String = row[1]
    let email: String = row[2]
    let player = Player(id: id, name: name, email: email)
    ...
}

When inserting values, use reusable prepared statements, and set statements values with an array:

// Strings & dictionaries
for player in players {
    try player.insert(db)
}

// Prepared statement
let insertStatement = db.prepareStatement("INSERT INTO player (name, email) VALUES (?, ?)")
for player in players {
    // Only use the unsafe arguments setter if you are sure that you provide
    // all statement arguments. A mistake can store unexpected values in
    // the database.
    insertStatement.unsafeSetArguments([player.name, player.email])
    try insertStatement.execute()
}

FAQ

How do I create a database in my application?

This question assumes that your application has to create a new database from scratch. If your app has to open an existing database that is embedded inside your application as a resource, see How do I open a database stored as a resource of my application? instead.

The database has to be stored in a valid place where it can be created and modified. For example, in the Application Support directory:

let databaseURL = try FileManager.default
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
let dbQueue = try DatabaseQueue(path: databaseURL.path)

How do I open a database stored as a resource of my application?

If your application does not need to modify the database, open a read-only connection to your resource:

var configuration = Configuration()
configuration.readonly = true
let dbPath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
let dbQueue = try DatabaseQueue(path: dbPath, configuration: configuration)

If the application should modify the database, you need to copy it to a place where it can be modified. For example, in the Application Support directory. Only then, open a connection:

let fileManager = FileManager.default
let dbPath = try fileManager
    .url(for: .applicationSupportDirectory, in: .userDomainMask, appropriateFor: nil, create: true)
    .appendingPathComponent("db.sqlite")
    .path
if !fileManager.fileExists(atPath: dbPath) {
    let dbResourcePath = Bundle.main.path(forResource: "db", ofType: "sqlite")!
    try fileManager.copyItem(atPath: dbResourcePath, toPath: dbPath)
}
let dbQueue = try DatabaseQueue(path: dbPath)

How do I close a database connection?

Database connections are managed by database queues and pools. A connection is closed when its database queue or pool is deallocated, and all usages of this connection are completed.

Database accesses that run in background threads postpone the closing of connections.

How do I print a request as SQL?

When you want to debug a request that does not deliver the expected results, you may want to print the SQL that is actually executed.

You can turn your request into a SQLRequest instance:

try dbQueue.read { db in
    let request = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")

    let sqlRequest = try SQLRequest(db, request: request)
    print(sqlRequest.sql)
    // Prints SELECT * FROM wine WHERE origin = ? ORDER BY price
    print(sqlRequest.arguments)
    // Prints ["Burgundy"]
}

Another option is to setup a tracing function that will print out all SQL requests executed by your application. You provide the trace function when you connect to the database:

var config = Configuration()
config.trace = { print($0) } // Prints all SQL statements
let dbQueue = try DatabaseQueue(path: dbPath, configuration: config)

try dbQueue.read { db in
    let wines = Wine
        .filter(Column("origin") == "Burgundy")
        .order(Column("price")
        .fetchAll(db)
    // Prints SELECT * FROM wine WHERE origin = 'Burgundy' ORDER BY price
}

Generic parameter ‘T’ could not be inferred

You may get this error when using the read and write methods of database queues and pools:

// Generic parameter 'T' could not be inferred
let x = try dbQueue.read { db in
    let result = try String.fetchOne(db, ...)
    return result
}

This is a Swift compiler issue (see SR-1570).

The general workaround is to explicitly declare the type of the closure result:

// General Workaround
let string = try dbQueue.read { db -> String? in
    let result = try String.fetchOne(db, ...)
    return result
}

You can also, when possible, write a single-line closure:

// Single-line closure workaround:
let string = try dbQueue.read { db in
    try String.fetchOne(db, ...)
}

SQLite error 10 "disk I/O error", SQLite error 23 "not authorized"

Those errors may be the sign that SQLite can’t access the database due to data protection.

When your application should be able to run in the background on a locked device, it has to catch this error, and, for example, wait for UIApplicationDelegate.applicationProtectedDataDidBecomeAvailable(_:) or UIApplicationProtectedDataDidBecomeAvailable notification and retry the failed database operation.

This error can also be prevented altogether by using a more relaxed file protection.

What Are Experimental Features?

Since GRDB 1.0, all backwards compatibility guarantees of semantic versioning apply: no breaking change will happen until the next major version of the library.

There is an exception, though: experimental features, marked with the ":fire: EXPERIMENTAL" badge. Those are advanced features that are too young, or lack user feedback. They are not stabilized yet.

Those experimental features are not protected by semantic versioning, and may break between two minor releases of the library. To help them becoming stable, your feedback is greatly appreciated.

Sample Code


Thanks

Legacy

Changes Tracking

This chapter has been renamed [Record Comparison].

Persistable Protocol

This protocol has been renamed [PersistableRecord] in GRDB 3.0.

RowConvertible Protocol

This protocol has been renamed [FetchableRecord] in GRDB 3.0.

TableMapping Protocol

This protocol has been renamed [TableRecord] in GRDB 3.0.

Customized Decoding of Database Rows

This chapter has been renamed [Beyond FetchableRecord].

Latest podspec

{
    "name": "GRDBPlus",
    "version": "3.6.1",
    "license": {
        "type": "MIT",
        "file": "LICENSE"
    },
    "summary": "A toolkit for SQLite databases, with a focus on application development.",
    "homepage": "https://github.com/groue/GRDB.swift",
    "authors": {
        "Gwendal Rouu00e9": "[email protected]"
    },
    "source": {
        "git": "https://github.com/groue/GRDB.swift.git",
        "tag": "v3.6.1"
    },
    "module_name": "GRDB",
    "platforms": {
        "ios": "11.4",
        "osx": "10.13",
        "watchos": "4.3"
    },
    "source_files": [
        "GRDB/**/*.swift",
        "Support/*.h"
    ],
    "module_map": "Support/module.modulemap",
    "frameworks": "Foundation",
    "libraries": "sqlite3",
    "xcconfig": {
        "OTHER_SWIFT_FLAGS": "$(inherited) -D SQLITE_ENABLE_FTS5"
    }
}

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