Data-Mapper ORM for TypeScript, ES7, ES6, ES5. Supports MySQL, PostgreSQL, MariaDB, SQLite, MS SQL Server, Oracle, MongoDB databases.
TypeORM is an Object-Relational Mapper (ORM) for Node.js that can be used with TypeScript or JavaScript (ES5, ES6, ES7, ES8). It supports both Active Record and Data Mapper patterns, unlike other JavaScript ORMs. You can use it with TypeScript and JavaScript (ES5, ES6, ES7, ES8). It's highly influenced by other ORMs, such as Hibernate, Doctrine, and Entity Framework.
Entity Definition
This code sample demonstrates how to define an entity in TypeORM. Entities are the equivalent of tables in a database, and each instance of an entity represents a row in the table.
import {Entity, PrimaryGeneratedColumn, Column} from 'typeorm';
@Entity()
export class User {
@PrimaryGeneratedColumn()
id: number;
@Column()
firstName: string;
@Column()
lastName: string;
@Column()
isActive: boolean;
}CRUD Operations
This code sample shows how to perform CRUD (Create, Read, Update, Delete) operations using the repository API provided by TypeORM.
import {getRepository} from 'typeorm';
import {User} from './entity/User';
async function createUser() {
const userRepository = getRepository(User);
const user = new User();
user.firstName = 'Timber';
user.lastName = 'Saw';
user.isActive = true;
await userRepository.save(user);
}
async function findUserById(id) {
const userRepository = getRepository(User);
return await userRepository.findOne(id);
}Data Querying
This code sample illustrates how to query data using the QueryBuilder API, which allows for building SQL queries in a programmatic and type-safe manner.
import {getConnection} from 'typeorm';
async function getUsersByName(firstName) {
const users = await getConnection()
.getRepository(User)
.createQueryBuilder('user')
.where('user.firstName = :firstName', { firstName })
.getMany();
return users;
}Transactions
This code sample demonstrates how to perform transactions, ensuring that all operations within the transaction block either complete successfully together or are all rolled back.
import {getConnection} from 'typeorm';
async function updateUserLastName(id, lastName) {
await getConnection().transaction(async transactionalEntityManager => {
const user = await transactionalEntityManager.findOne(User, id);
user.lastName = lastName;
await transactionalEntityManager.save(user);
});
}Migrations
This code sample shows how to define a migration class in TypeORM. Migrations are a way to manage database schema changes and can be automatically generated or manually written.
import {MigrationInterface, QueryRunner} from 'typeorm';
export class CreateUserTable1588102412341 implements MigrationInterface {
public async up(queryRunner: QueryRunner): Promise<void> {
await queryRunner.query(`CREATE TABLE user (id int PRIMARY KEY, firstName varchar(255), lastName varchar(255))`);
}
public async down(queryRunner: QueryRunner): Promise<void> {
await queryRunner.query('DROP TABLE user');
}
}Sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite, and Microsoft SQL Server. It features solid transaction support, relations, eager and lazy loading, read replication, and more. Compared to TypeORM, Sequelize has been around for longer and has a larger community, but it doesn't have as strong TypeScript support.
Bookshelf is a JavaScript ORM for Node.js, built on the Knex SQL query builder. It features a simple and intuitive API and supports transactions, eager/nested-eager relation loading, and plugins. Unlike TypeORM, Bookshelf follows a more traditional JavaScript style and doesn't emphasize TypeScript integration.
TypeORM is an ORM that can run in NodeJS, Browser, Cordova, PhoneGap, Ionic, React Native, NativeScript, Expo, and Electron platforms and can be used with TypeScript and JavaScript (ES5, ES6, ES7, ES8). Its goal is to always support the latest JavaScript features and provide additional features that help you to develop any kind of application that uses databases - from small applications with a few tables to large scale enterprise applications with multiple databases.
TypeORM supports both Active Record and Data Mapper patterns, unlike all other JavaScript ORMs currently in existence, which means you can write high quality, loosely coupled, scalable, maintainable applications the most productive way.
TypeORM is highly influenced by other ORMs, such as Hibernate, Doctrine and Entity Framework.
And more...
With TypeORM your models look like this:
import { Entity, PrimaryGeneratedColumn, Column } from "typeorm"
@Entity()
export class User {
@PrimaryGeneratedColumn()
id: number
@Column()
firstName: string
@Column()
lastName: string
@Column()
age: number
}
And your domain logic looks like this:
const userRepository = MyDataSource.getRepository(User)
const user = new User()
user.firstName = "Timber"
user.lastName = "Saw"
user.age = 25
await userRepository.save(user)
const allUsers = await userRepository.find()
const firstUser = await userRepository.findOneBy({
id: 1,
}) // find by id
const timber = await userRepository.findOneBy({
firstName: "Timber",
lastName: "Saw",
}) // find by firstName and lastName
await userRepository.remove(timber)
Alternatively, if you prefer to use the ActiveRecord implementation, you can use it as well:
import { Entity, PrimaryGeneratedColumn, Column, BaseEntity } from "typeorm"
@Entity()
export class User extends BaseEntity {
@PrimaryGeneratedColumn()
id: number
@Column()
firstName: string
@Column()
lastName: string
@Column()
age: number
}
And your domain logic will look this way:
const user = new User()
user.firstName = "Timber"
user.lastName = "Saw"
user.age = 25
await user.save()
const allUsers = await User.find()
const firstUser = await User.findOneBy({
id: 1,
})
const timber = await User.findOneBy({
firstName: "Timber",
lastName: "Saw"
})
await timber.remove()
Install the npm package:
npm install typeorm --save
You need to install reflect-metadata shim:
npm install reflect-metadata --save
and import it somewhere in the global place of your app (for example in app.ts):
import "reflect-metadata"
You may need to install node typings:
npm install @types/node --save-dev
Install a database driver:
for MySQL or MariaDB
npm install mysql --save (you can install mysql2 instead as well)
for PostgreSQL or CockroachDB
npm install pg --save
for SQLite
npm install sqlite3 --save
for Microsoft SQL Server
npm install mssql --save
for sql.js
npm install sql.js --save
for Oracle
npm install oracledb --save
To make the Oracle driver work, you need to follow the installation instructions from their site.
for SAP Hana
npm install @sap/hana-client
npm install hdb-pool
SAP Hana support made possible by the sponsorship of Neptune Software.
for Google Cloud Spanner
npm install @google-cloud/spanner --save
Provide authentication credentials to your application code
by setting the environment variable GOOGLE_APPLICATION_CREDENTIALS:
# Linux/macOS
export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"
# Windows
set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH
# Replace KEY_PATH with the path of the JSON file that contains your service account key.
To use Spanner with the emulator you should set SPANNER_EMULATOR_HOST environment variable:
# Linux/macOS
export SPANNER_EMULATOR_HOST=localhost:9010
# Windows
set SPANNER_EMULATOR_HOST=localhost:9010
for MongoDB (experimental)
npm install mongodb@^3.6.0 --save
for NativeScript, react-native and Cordova
Install only one of them, depending on which database you use.
Also, make sure you are using TypeScript version 4.5 or higher,
and you have enabled the following settings in tsconfig.json:
"emitDecoratorMetadata": true,
"experimentalDecorators": true,
You may also need to enable es6 in the lib section of compiler options, or install es6-shim from @types.
The quickest way to get started with TypeORM is to use its CLI commands to generate a starter project. Quick start works only if you are using TypeORM in a NodeJS application. If you are using other platforms, proceed to the step-by-step guide.
To create a new project using CLI, run the following command:
npx typeorm init --name MyProject --database postgres
Where name is the name of your project and database is the database you'll use.
Database can be one of the following values: mysql, mariadb, postgres, cockroachdb, sqlite, mssql, sap, spanner, oracle, mongodb,
cordova, react-native, expo, nativescript.
This command will generate a new project in the MyProject directory with the following files:
MyProject
├── src // place of your TypeScript code
│ ├── entity // place where your entities (database models) are stored
│ │ └── User.ts // sample entity
│ ├── migration // place where your migrations are stored
│ ├── data-source.ts // data source and all connection configuration
│ └── index.ts // start point of your application
├── .gitignore // standard gitignore file
├── package.json // node module dependencies
├── README.md // simple readme file
└── tsconfig.json // TypeScript compiler options
You can also run
typeorm initon an existing node project, but be careful - it may override some files you already have.
The next step is to install new project dependencies:
cd MyProject
npm install
After you have all dependencies installed, edit the data-source.ts file and put your own database connection configuration options in there:
export const AppDataSource = new DataSource({
type: "postgres",
host: "localhost",
port: 5432,
username: "test",
password: "test",
database: "test",
synchronize: true,
logging: true,
entities: [Post, Category],
subscribers: [],
migrations: [],
})
Particularly, most of the time you'll only need to configure
host, username, password, database and maybe port options.
Once you finish with configuration and all node modules are installed, you can run your application:
npm start
That's it, your application should successfully run and insert a new user into the database. You can continue to work with this project and integrate other modules you need and start creating more entities.
You can generate an ESM project by running
npx typeorm init --name MyProject --database postgres --module esmcommand.
You can generate an even more advanced project with express installed by running
npx typeorm init --name MyProject --database mysql --expresscommand.
You can generate a docker-compose file by running
npx typeorm init --name MyProject --database postgres --dockercommand.
What are you expecting from ORM? First of all, you are expecting it will create database tables for you and find / insert / update / delete your data without the pain of having to write lots of hardly maintainable SQL queries. This guide will show you how to set up TypeORM from scratch and make it do what you are expecting from an ORM.
Working with a database starts from creating tables. How do you tell TypeORM to create a database table? The answer is - through the models. Your models in your app are your database tables.
For example, you have a Photo model:
export class Photo {
id: number
name: string
description: string
filename: string
views: number
isPublished: boolean
}
And you want to store photos in your database. To store things in the database, first, you need a database table, and database tables are created from your models. Not all models, but only those you define as entities.
Entity is your model decorated by an @Entity decorator.
A database table will be created for such models.
You work with entities everywhere in TypeORM.
You can load/insert/update/remove and perform other operations with them.
Let's make our Photo model an entity:
import { Entity } from "typeorm"
@Entity()
export class Photo {
id: number
name: string
description: string
filename: string
views: number
isPublished: boolean
}
Now, a database table will be created for the Photo entity and we'll be able to work with it anywhere in our app.
We have created a database table, however, what table can exist without columns?
Let's create few columns in our database table.
To add database columns, you simply need to decorate an entity's properties you want to make into a column
with a @Column decorator.
import { Entity, Column } from "typeorm"
@Entity()
export class Photo {
@Column()
id: number
@Column()
name: string
@Column()
description: string
@Column()
filename: string
@Column()
views: number
@Column()
isPublished: boolean
}
Now id, name, description, filename, views and isPublished columns will be added to the photo table.
Column types in the database are inferred from the property types you used, e.g.
number will be converted into integer, string into varchar, boolean into bool, etc.
But you can use any column type your database supports by explicitly specifying a column type into the @Column decorator.
We generated a database table with columns, but there is one thing left. Each database table must have a column with a primary key.
Each entity must have at least one primary key column.
This is a requirement and you can't avoid it.
To make a column a primary key, you need to use the @PrimaryColumn decorator.
import { Entity, Column, PrimaryColumn } from "typeorm"
@Entity()
export class Photo {
@PrimaryColumn()
id: number
@Column()
name: string
@Column()
description: string
@Column()
filename: string
@Column()
views: number
@Column()
isPublished: boolean
}
Now, let's say you want your id column to be auto-generated (this is known as auto-increment / sequence / serial / generated identity column).
To do that, you need to change the @PrimaryColumn decorator to a @PrimaryGeneratedColumn decorator:
import { Entity, Column, PrimaryGeneratedColumn } from "typeorm"
@Entity()
export class Photo {
@PrimaryGeneratedColumn()
id: number
@Column()
name: string
@Column()
description: string
@Column()
filename: string
@Column()
views: number
@Column()
isPublished: boolean
}
Next, let's fix our data types. By default, the string is mapped to a varchar(255)-like type (depending on the database type). The number is mapped to an integer-like type (depending on the database type). We don't want all our columns to be limited varchars or integers. Let's setup correct data types:
import { Entity, Column, PrimaryGeneratedColumn } from "typeorm"
@Entity()
export class Photo {
@PrimaryGeneratedColumn()
id: number
@Column({
length: 100,
})
name: string
@Column("text")
description: string
@Column()
filename: string
@Column("double")
views: number
@Column()
isPublished: boolean
}
Column types are database-specific. You can set any column type your database supports. More information on supported column types can be found here.
DataSourceNow, when our entity is created, let's create index.ts file and set up our DataSource there:
import "reflect-metadata"
import { DataSource } from "typeorm"
import { Photo } from "./entity/Photo"
const AppDataSource = new DataSource({
type: "postgres",
host: "localhost",
port: 5432,
username: "root",
password: "admin",
database: "test",
entities: [Photo],
synchronize: true,
logging: false,
})
// to initialize initial connection with the database, register all entities
// and "synchronize" database schema, call "initialize()" method of a newly created database
// once in your application bootstrap
AppDataSource.initialize()
.then(() => {
// here you can start to work with your database
})
.catch((error) => console.log(error))
We are using Postgres in this example, but you can use any other supported database.
To use another database, simply change the type in the options to the database type you are using:
mysql, mariadb, postgres, cockroachdb, sqlite, mssql, oracle, sap, spanner, cordova, nativescript, react-native,
expo, or mongodb.
Also make sure to use your own host, port, username, password and database settings.
We added our Photo entity to the list of entities for this data source. Each entity you are using in your connection must be listed there.
Setting synchronize makes sure your entities will be synced with the database, every time you run the application.
Now if you run your index.ts, a connection with the database will be initialized and a database table for your photos will be created.
+-------------+--------------+----------------------------+
| photo |
+-------------+--------------+----------------------------+
| id | int(11) | PRIMARY KEY AUTO_INCREMENT |
| name | varchar(100) | |
| description | text | |
| filename | varchar(255) | |
| views | int(11) | |
| isPublished | boolean | |
+-------------+--------------+----------------------------+
Now let's create a new photo to save it in the database:
import { Photo } from "./entity/Photo"
import { AppDataSource } from "./index"
const photo = new Photo()
photo.name = "Me and Bears"
photo.description = "I am near polar bears"
photo.filename = "photo-with-bears.jpg"
photo.views = 1
photo.isPublished = true
await AppDataSource.manager.save(photo)
console.log("Photo has been saved. Photo id is", photo.id)
Once your entity is saved it will get a newly generated id.
save method returns an instance of the same object you pass to it.
It's not a new copy of the object, it modifies its "id" and returns it.
We just created a new photo and saved it in the database.
We used EntityManager to save it.
Using entity manager you can manipulate any entity in your app.
For example, let's load our saved entity:
import { Photo } from "./entity/Photo"
import { AppDataSource } from "./index"
const savedPhotos = await AppDataSource.manager.find(Photo)
console.log("All photos from the db: ", savedPhotos)
savedPhotos will be an array of Photo objects with the data loaded from the database.
Learn more about EntityManager here.
Now let's refactor our code and use Repository instead of EntityManager.
Each entity has its own repository which handles all operations with its entity.
When you deal with entities a lot, Repositories are more convenient to use than EntityManagers:
import { Photo } from "./entity/Photo"
import { AppDataSource } from "./index"
const photo = new Photo()
photo.name = "Me and Bears"
photo.description = "I am near polar bears"
photo.filename = "photo-with-bears.jpg"
photo.views = 1
photo.isPublished = true
const photoRepository = AppDataSource.getRepository(Photo)
await photoRepository.save(photo)
console.log("Photo has been saved")
const savedPhotos = await photoRepository.find()
console.log("All photos from the db: ", savedPhotos)
Learn more about Repository here.
Let's try more load operations using the Repository:
import { Photo } from "./entity/Photo"
import { AppDataSource } from "./index"
const photoRepository = AppDataSource.getRepository(Photo)
const allPhotos = await photoRepository.find()
console.log("All photos from the db: ", allPhotos)
const firstPhoto = await photoRepository.findOneBy({
id: 1,
})
console.log("First photo from the db: ", firstPhoto)
const meAndBearsPhoto = await photoRepository.findOneBy({
name: "Me and Bears",
})
console.log("Me and Bears photo from the db: ", meAndBearsPhoto)
const allViewedPhotos = await photoRepository.findBy({ views: 1 })
console.log("All viewed photos: ", allViewedPhotos)
const allPublishedPhotos = await photoRepository.findBy({ isPublished: true })
console.log("All published photos: ", allPublishedPhotos)
const [photos, photosCount] = await photoRepository.findAndCount()
console.log("All photos: ", photos)
console.log("Photos count: ", photosCount)
Now let's load a single photo from the database, update it and save it:
import { Photo } from "./entity/Photo"
import { AppDataSource } from "./index"
const photoRepository = AppDataSource.getRepository(Photo)
const photoToUpdate = await photoRepository.findOneBy({
id: 1,
})
photoToUpdate.name = "Me, my friends and polar bears"
await photoRepository.save(photoToUpdate)
Now photo with id = 1 will be updated in the database.
Now let's remove our photo from the database:
import { Photo } from "./entity/Photo"
import { AppDataSource } from "./index"
const photoRepository = AppDataSource.getRepository(Photo)
const photoToRemove = await photoRepository.findOneBy({
id: 1,
})
await photoRepository.remove(photoToRemove)
Now photo with id = 1 will be removed from the database.
Let's create a one-to-one relationship with another class.
Let's create a new class in PhotoMetadata.ts. This PhotoMetadata class is supposed to contain our photo's additional meta-information:
import {
Entity,
Column,
PrimaryGeneratedColumn,
OneToOne,
JoinColumn,
} from "typeorm"
import { Photo } from "./Photo"
@Entity()
export class PhotoMetadata {
@PrimaryGeneratedColumn()
id: number
@Column("int")
height: number
@Column("int")
width: number
@Column()
orientation: string
@Column()
compressed: boolean
@Column()
comment: string
@OneToOne(() => Photo)
@JoinColumn()
photo: Photo
}
Here, we are using a new decorator called @OneToOne. It allows us to create a one-to-one relationship between two entities.
type => Photo is a function that returns the class of the entity with which we want to make our relationship.
We are forced to use a function that returns a class, instead of using the class directly, because of the language specifics.
We can also write it as () => Photo, but we use type => Photo as a convention to increase code readability.
The type variable itself does not contain anything.
We also add a @JoinColumn decorator, which indicates that this side of the relationship will own the relationship.
Relations can be unidirectional or bidirectional.
Only one side of relational can be owning.
Using @JoinColumn decorator is required on the owner side of the relationship.
If you run the app, you'll see a newly generated table, and it will contain a column with a foreign key for the photo relation:
+-------------+--------------+----------------------------+
| photo_metadata |
+-------------+--------------+----------------------------+
| id | int(11) | PRIMARY KEY AUTO_INCREMENT |
| height | int(11) | |
| width | int(11) | |
| comment | varchar(255) | |
| compressed | boolean | |
| orientation | varchar(255) | |
| photoId | int(11) | FOREIGN KEY |
+-------------+--------------+----------------------------+
Now let's save a photo, its metadata and attach them to each other.
import { Photo } from "./entity/Photo"
import { PhotoMetadata } from "./entity/PhotoMetadata"
// create a photo
const photo = new Photo()
photo.name = "Me and Bears"
photo.description = "I am near polar bears"
photo.filename = "photo-with-bears.jpg"
photo.views = 1
photo.isPublished = true
// create a photo metadata
const metadata = new PhotoMetadata()
metadata.height = 640
metadata.width = 480
metadata.compressed = true
metadata.comment = "cybershoot"
metadata.orientation = "portrait"
metadata.photo = photo // this way we connect them
// get entity repositories
const photoRepository = AppDataSource.getRepository(Photo)
const metadataRepository = AppDataSource.getRepository(PhotoMetadata)
// first we should save a photo
await photoRepository.save(photo)
// photo is saved. Now we need to save a photo metadata
await metadataRepository.save(metadata)
// done
console.log(
"Metadata is saved, and the relation between metadata and photo is created in the database too",
)
Relations can be unidirectional or bidirectional. Currently, our relation between PhotoMetadata and Photo is unidirectional. The owner of the relation is PhotoMetadata, and Photo doesn't know anything about PhotoMetadata. This makes it complicated to access PhotoMetadata from the Photo side. To fix this issue we should add an inverse relation, and make relations between PhotoMetadata and Photo bidirectional. Let's modify our entities:
import {
Entity,
Column,
PrimaryGeneratedColumn,
OneToOne,
JoinColumn,
} from "typeorm"
import { Photo } from "./Photo"
@Entity()
export class PhotoMetadata {
/* ... other columns */
@OneToOne(() => Photo, (photo) => photo.metadata)
@JoinColumn()
photo: Photo
}
import { Entity, Column, PrimaryGeneratedColumn, OneToOne } from "typeorm"
import { PhotoMetadata } from "./PhotoMetadata"
@Entity()
export class Photo {
/* ... other columns */
@OneToOne(() => PhotoMetadata, (photoMetadata) => photoMetadata.photo)
metadata: PhotoMetadata
}
photo => photo.metadata is a function that returns the name of the inverse side of the relation.
Here we show that the metadata property of the Photo class is where we store PhotoMetadata in the Photo class.
Instead of passing a function that returns a property of the photo, you could alternatively simply pass a string to @OneToOne decorator, like "metadata".
But we used this function-typed approach to make our refactoring easier.
Note that we should use the @JoinColumn decorator only on one side of a relation.
Whichever side you put this decorator on will be the owning side of the relationship.
The owning side of a relationship contains a column with a foreign key in the database.
If you use ESM in your TypeScript project, you should use the Relation wrapper type in relation properties to avoid circular dependency issues.
Let's modify our entities:
import {
Entity,
Column,
PrimaryGeneratedColumn,
OneToOne,
JoinColumn,
Relation,
} from "typeorm"
import { Photo } from "./Photo"
@Entity()
export class PhotoMetadata {
/* ... other columns */
@OneToOne(() => Photo, (photo) => photo.metadata)
@JoinColumn()
photo: Relation<Photo>
}
import {
Entity,
Column,
PrimaryGeneratedColumn,
OneToOne,
Relation,
} from "typeorm"
import { PhotoMetadata } from "./PhotoMetadata"
@Entity()
export class Photo {
/* ... other columns */
@OneToOne(() => PhotoMetadata, (photoMetadata) => photoMetadata.photo)
metadata: Relation<PhotoMetadata>
}
Now let's load our photo and its photo metadata in a single query.
There are two ways to do it - using find* methods or using QueryBuilder functionality.
Let's use find* methods first.
find* methods allow you to specify an object with the FindOneOptions / FindManyOptions interface.
import { Photo } from "./entity/Photo"
import { PhotoMetadata } from "./entity/PhotoMetadata"
import { AppDataSource } from "./index"
const photoRepository = AppDataSource.getRepository(Photo)
const photos = await photoRepository.find({
relations: {
metadata: true,
},
})
Here, photos will contain an array of photos from the database, and each photo will contain its photo metadata. Learn more about Find Options in this documentation.
Using find options is good and dead simple, but if you need a more complex query, you should use QueryBuilder instead.
QueryBuilder allows more complex queries to be used in an elegant way:
import { Photo } from "./entity/Photo"
import { PhotoMetadata } from "./entity/PhotoMetadata"
import { AppDataSource } from "./index"
const photos = await AppDataSource.getRepository(Photo)
.createQueryBuilder("photo")
.innerJoinAndSelect("photo.metadata", "metadata")
.getMany()
QueryBuilder allows the creation and execution of SQL queries of almost any complexity.
When you work with QueryBuilder, think like you are creating an SQL query.
In this example, "photo" and "metadata" are aliases applied to selected photos.
You use aliases to access columns and properties of the selected data.
We can set up cascade options in our relations, in the cases when we want our related object to be saved whenever the other object is saved.
Let's change our photo's @OneToOne decorator a bit:
export class Photo {
// ... other columns
@OneToOne(() => PhotoMetadata, (metadata) => metadata.photo, {
cascade: true,
})
metadata: PhotoMetadata
}
Using cascade allows us not to separately save photo and separately save metadata objects now.
Now we can simply save a photo object, and the metadata object will be saved automatically because of cascade options.
import { AppDataSource } from "./index"
// create photo object
const photo = new Photo()
photo.name = "Me and Bears"
photo.description = "I am near polar bears"
photo.filename = "photo-with-bears.jpg"
photo.isPublished = true
// create photo metadata object
const metadata = new PhotoMetadata()
metadata.height = 640
metadata.width = 480
metadata.compressed = true
metadata.comment = "cybershoot"
metadata.orientation = "portrait"
photo.metadata = metadata // this way we connect them
// get repository
const photoRepository = AppDataSource.getRepository(Photo)
// saving a photo also save the metadata
await photoRepository.save(photo)
console.log("Photo is saved, photo metadata is saved too.")
Notice that we now set the photo's metadata property, instead of the metadata's photo property as before. The cascade feature only works if you connect the photo to its metadata from the photo's side. If you set the metadata's side, the metadata would not be saved automatically.
Let's create a many-to-one/one-to-many relation.
Let's say a photo has one author, and each author can have many photos.
First, let's create an Author class:
import {
Entity,
Column,
PrimaryGeneratedColumn,
OneToMany,
JoinColumn,
} from "typeorm"
import { Photo } from "./Photo"
@Entity()
export class Author {
@PrimaryGeneratedColumn()
id: number
@Column()
name: string
@OneToMany(() => Photo, (photo) => photo.author) // note: we will create author property in the Photo class below
photos: Photo[]
}
Author contains an inverse side of a relation.
OneToMany is always an inverse side of the relation, and it can't exist without ManyToOne on the other side of the relation.
Now let's add the owner side of the relation into the Photo entity:
import { Entity, Column, PrimaryGeneratedColumn, ManyToOne } from "typeorm"
import { PhotoMetadata } from "./PhotoMetadata"
import { Author } from "./Author"
@Entity()
export class Photo {
/* ... other columns */
@ManyToOne(() => Author, (author) => author.photos)
author: Author
}
In many-to-one / one-to-many relation, the owner side is always many-to-one.
It means that the class that uses @ManyToOne will store the id of the related object.
After you run the application, the ORM will create the author table:
+-------------+--------------+----------------------------+
| author |
+-------------+--------------+----------------------------+
| id | int(11) | PRIMARY KEY AUTO_INCREMENT |
| name | varchar(255) | |
+-------------+--------------+----------------------------+
It will also modify the photo table, adding a new author column and creating a foreign key for it:
+-------------+--------------+----------------------------+
| photo |
+-------------+--------------+----------------------------+
| id | int(11) | PRIMARY KEY AUTO_INCREMENT |
| name | varchar(255) | |
| description | varchar(255) | |
| filename | varchar(255) | |
| isPublished | boolean | |
| authorId | int(11) | FOREIGN KEY |
+-------------+--------------+----------------------------+
Let's create a many-to-many relation.
Let's say a photo can be in many albums, and each album can contain many photos.
Let's create an Album class:
import {
Entity,
PrimaryGeneratedColumn,
Column,
ManyToMany,
JoinTable,
} from "typeorm"
@Entity()
export class Album {
@PrimaryGeneratedColumn()
id: number
@Column()
name: string
@ManyToMany(() => Photo, (photo) => photo.albums)
@JoinTable()
photos: Photo[]
}
@JoinTable is required to specify that this is the owner side of the relationship.
Now let's add the inverse side of our relation to the Photo class:
export class Photo {
// ... other columns
@ManyToMany(() => Album, (album) => album.photos)
albums: Album[]
}
After you run the application, the ORM will create a album_photos_photo_albums junction table:
+-------------+--------------+----------------------------+
| album_photos_photo_albums |
+-------------+--------------+----------------------------+
| album_id | int(11) | PRIMARY KEY FOREIGN KEY |
| photo_id | int(11) | PRIMARY KEY FOREIGN KEY |
+-------------+--------------+----------------------------+
Don't forget to register the Album class with your connection in the ORM:
const options: DataSourceOptions = {
// ... other options
entities: [Photo, PhotoMetadata, Author, Album],
}
Now let's insert albums and photos to our database:
import { AppDataSource } from "./index"
// create a few albums
const album1 = new Album()
album1.name = "Bears"
await AppDataSource.manager.save(album1)
const album2 = new Album()
album2.name = "Me"
await AppDataSource.manager.save(album2)
// create a few photos
const photo = new Photo()
photo.name = "Me and Bears"
photo.description = "I am near polar bears"
photo.filename = "photo-with-bears.jpg"
photo.views = 1
photo.isPublished = true
photo.albums = [album1, album2]
await AppDataSource.manager.save(photo)
// now our photo is saved and albums are attached to it
// now lets load them:
const loadedPhoto = await AppDataSource.getRepository(Photo).findOne({
where: {
id: 1,
},
relations: {
albums: true,
},
})
loadedPhoto will be equal to:
{
id: 1,
name: "Me and Bears",
description: "I am near polar bears",
filename: "photo-with-bears.jpg",
albums: [{
id: 1,
name: "Bears"
}, {
id: 2,
name: "Me"
}]
}
You can use QueryBuilder to build SQL queries of almost any complexity. For example, you can do this:
const photos = await AppDataSource.getRepository(Photo)
.createQueryBuilder("photo") // first argument is an alias. Alias is what you are selecting - photos. You must specify it.
.innerJoinAndSelect("photo.metadata", "metadata")
.leftJoinAndSelect("photo.albums", "album")
.where("photo.isPublished = true")
.andWhere("(photo.name = :photoName OR photo.name = :bearName)")
.orderBy("photo.id", "DESC")
.skip(5)
.take(10)
.setParameters({ photoName: "My", bearName: "Mishka" })
.getMany()
This query selects all published photos with "My" or "Mishka" names. It will select results from position 5 (pagination offset) and will select only 10 results (pagination limit). The selection result will be ordered by id in descending order. The photo's albums will be left joined and their metadata will be inner joined.
You'll use the query builder in your application a lot. Learn more about QueryBuilder here.
Take a look at the samples in sample for examples of usage.
There are a few repositories which you can clone and start with:
There are several extensions that simplify working with TypeORM and integrating it with other modules:
data-source.ts after generating migrations/entities - typeorm-codebase-syncrelations objects - typeorm-relationsrelations based on a GraphQL query - typeorm-relations-graphqlLearn about contribution here and how to setup your development environment here.
This project exists thanks to all the people who contribute:
Open source is hard and time-consuming. If you want to invest in TypeORM's future you can become a sponsor and allow our core team to spend more time on TypeORM's improvements and new features. Become a sponsor
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0.3.11 (2022-12-03)
init command (#9422) (0984307)FAQs
Data-Mapper ORM for TypeScript, ES7, ES6, ES5. Supports MySQL, PostgreSQL, MariaDB, SQLite, MS SQL Server, Oracle, MongoDB databases.
The npm package typeorm receives a total of 1,350,200 weekly downloads. As such, typeorm popularity was classified as popular.
We found that typeorm demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
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