Neo4j driver for MikroORM | mikro-orm-neo4j

Graph-native relationships

Directed edges with a real type, traversal filters at any depth, and relationship entities for edges that carry properties of their own.

Filters that compile to Cypher

The whole MikroORM operator surface — including the list and collection operators — mapped onto Cypher, with the untranslatable ones refused by name instead of ignored.

Full-text search, declared where it is searched

A search field typed as the search itself backs a real Neo4j fulltext index: analyzers, weights, interface-wide indexes and the matching GraphQL directive.

Cursor-based streaming

em.stream() reads through a Bolt cursor instead of buffering: bounded memory, populated relations merged as rows arrive, and a cursor you can close.

Multi-tenancy as soft subgraphs

MikroORM's schema option — fixed or wildcard — scoping writes, reads and both ends of every relationship. Onboarding a tenant costs zero migrations.

Typed stored routines

APOC, GDS and the built-ins declared once, called like any ORM method, composed into queries — and generated straight from the server.

The ORM you already know

Entities, the EntityManager, repositories, the unit of work and the identity map all behave the way MikroORM documents them. What changes is what runs: a filter becomes a Cypher pattern, a many-to-many becomes an edge, and a populate becomes a traversal.

import { MikroORM } from 'mikro-orm-neo4j';

const orm = await MikroORM.init({
  clientUrl: 'bolt://localhost:7687',
  user: 'neo4j',
  password: 'password',
  entities: [Book, Author, Tag],
});

// Filters traverse the graph — each hop becomes a pattern subquery.
const books = await orm.em.find(
  Book,
  { price: { $gte: 10 }, author: { name: 'Ann' }, tags: { $some: { name: 'Fiction' } } },
  { populate: ['author'], orderBy: { title: 'ASC' }, limit: 20 },
);

Start here, or jump to what each filter operator compiles to.