Usage with MongoDB

To use MikroORM with mongo database, do not forget to install @mikro-orm/mongodb dependency. Then call MikroORM.init() as part of bootstrapping your app:

To access driver specific methods like em.aggregate() we need to specify the driver type when calling MikroORM.init<D>(). Alternatively we can cast the orm.em to EntityManager exported from the driver package:

import { EntityManager } from '@mikro-orm/mongodb';
const em = orm.em as EntityManager;
const qb = em.aggregate(...);

We need to use clientUrl to set up hosts, using host or port is not supported.

import { MikroORM } from '@mikro-orm/mongodb'; // or any other driver package

const orm = await MikroORM.init({
  entities: [Author, Book, ...],
  dbName: 'my-db-name',
  clientUrl: '...',
});
console.log(orm.em); // access EntityManager via `em` property

Defining entity​

When defining entity, do not forget to define primary key like this:

@PrimaryKey()
_id: ObjectId;

@SerializedPrimaryKey()
id!: string; // won't be saved in the database

Only _id: ObjectId will be saved in the database. id: string is virtual and is also optional.

ObjectId and string id duality​

Every entity has both ObjectId and string id available, also all methods of EntityManager and EntityRepository supports querying by both of them.

const author = orm.em.getReference('...id...');
console.log(author.id);  // returns '...id...'
console.log(author._id); // returns ObjectId('...id...')

// all of those will return the same results
const article = '...article id...'; // string id
const book = '...book id...'; // string id
const repo = orm.em.getRepository(Author);
const foo1 = await repo.find({ id: { $in: [article] }, favouriteBook: book });
const bar1 = await repo.find({ id: { $in: [new ObjectId(article)] }, favouriteBook: new ObjectId(book) });
const foo2 = await repo.find({ _id: { $in: [article] }, favouriteBook: book });
const bar2 = await repo.find({ _id: { $in: [new ObjectId(article)] }, favouriteBook: new ObjectId(book) });

ManyToMany collections with inlined pivot array​

As opposed to SQL drivers that use pivot tables, in mongo we can leverage available array type to store array of collection items (identifiers). This approach has two main benefits:

1. Collection is stored on owning side entity, so we know how many items are there even before initializing the collection.
2. As there are no pivot tables, resulting database queries are much simpler.

Transactions​

Starting with v3.4, MongoDB driver supports transactions. To use transactions, there are several things you need to respect:

• you need to use replica set (see run-rs)
• implicit transactions are disabled by default
  • use implicitTransactions: true to enable them globally
  • or use explicit transaction demarcation via em.transactional()
• you need to explicitly create all collections before working with them
  • use orm.schema.createSchema() method to do so

# first create replica set
$ run-rs -v 4.2.3

// make sure to import from the MongoDriver package
import { MikroORM } from '@mikro-orm/mongodb';

const orm = await MikroORM.init({
  entities: [Author, Book, ...],
  clientUrl: 'mongodb://localhost:27017,localhost:27018,localhost:27019/my-db-name?replicaSet=rs0',
  implicitTransactions: true, // defaults to false
});

await orm.schema.createSchema();

Indexes​

Starting with v3.4, MongoDB driver supports indexes and unique constraints. You can use @Index() and @Unique() as described in Defining Entities section. To automatically create new indexes when initializing the ORM, you need to enable ensureIndexes option.

const orm = await MikroORM.init({
  entities: [Author, Book, ...],
  dbName: 'my-db-name',
  ensureIndexes: true, // defaults to false
});

Alternatively you can call ensureIndexes() method on the SchemaGenerator:

SchemaGenerator support for mongo was introduced in v5.

await orm.schema.ensureIndexes();

You can pass additional index/unique options via options parameter:

@Unique({ options: { partialFilterExpression: { name: { $exists: true } } }})

You can also create text indexes by passing type parameter:

@Index({ properties: ['name', 'caption'], type: 'text' })

If you provide only options in the index definition, it will be used as is, this allows to define any kind of index:

@Index({ options: { point: '2dsphere', title: -1 } })

To set index weights, you can pass a tuple to the options parameter:

@Index({ options: [
  { title: 'text', perex: 'text', key: 1 },
  { weights: { title: 10, perex: 5 } },
] })

Native collection methods​

Sometimes you need to perform some bulk operation, or you just want to populate your database with initial fixtures. Using ORM for such operations can bring unnecessary boilerplate code. In this case, you can use one of insert/nativeUpdate/nativeDelete methods:

em.insert<T extends AnyEntity>(entityName: string, data: any): Promise<IPrimaryKey>;
em.nativeUpdate<T extends AnyEntity>(entityName: string, where: FilterQuery<T>, data: any): Promise<number>;
em.nativeDelete<T extends AnyEntity>(entityName: string, where: FilterQuery<T> | any): Promise<number>;

Those methods execute native driver methods like Mongo's insertOne/updateMany/deleteMany collection methods respectively. This is common interface for all drivers, so for MySQL driver, it will fire native SQL queries. Keep in mind that they do not hydrate results to entities, and they do not trigger lifecycle hooks.

They are also available as EntityRepository shortcuts:

EntityRepository.insert(data: any): Promise<IPrimaryKey>;
EntityRepository.nativeUpdate(where: FilterQuery<T>, data: any): Promise<number>;
EntityRepository.nativeDelete(where: FilterQuery<T> | any): Promise<number>;

There is also shortcut for calling aggregate method:

em.aggregate(entityName: string, pipeline: any[]): Promise<any[]>;
EntityRepository.aggregate(pipeline: any[]): Promise<any[]>;