# neo4j-contrib/neomodel

An Object Graph Mapper (OGM) for the Neo4j graph database.

Repository: https://github.com/neo4j-contrib/neomodel
Canonical: https://ross.abutalabs.com/products/neomodel
Homepage: https://neomodel.readthedocs.io
Language: Python
License: MIT
License Family: permissive
Topics: neo4j, python, ogm
Last push: 2026-08-26T12:07:19+00:00

## Health v2 (maintenance only)
Score: 95/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 87, longevity 100
- inputs: {"age_days": 5103, "days_push": 7, "days_rel": 7, "gap_med": 45, "n_releases_24m": 16}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1088, forks 243 (observed 2026-08-28T04:03:32.373599+00:00)

## What it is
Neomodel is an Object Graph Mapper (OGM) for the Neo4j graph database, built on the official Neo4j Python driver. It provides class-based model definitions, a powerful query API, schema enforcement, transaction support, and native vector and full-text semantic indexes.

## Use cases
- map python classes to neo4j graph nodes
- query a graph database without writing raw cypher
- use neo4j as the database for a django app
- store and query embeddings with vector indexes in neo4j
- model relationships between entities in a graph database from python

## When to choose
- you use neo4j and want an ORM-like abstraction in python
- you want schema enforcement, hooks, and transactions over the graph
- you need django integration with neo4j

## When to avoid
- you use a relational or document database instead of neo4j
- you prefer writing raw cypher queries directly
- you need a mapper for a different graph database

## Facets
- artifact type: library
- maturity: active
- function: orm, database-driver, database
- domain: databases, developer-tools, web-development
- platform: python, cross-platform
- tags: neo4j, ogm, graph-database, cypher, django-integration, vector-index

## Member repositories
- neo4j-contrib/neomodel (main) score 95

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:32.373599+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:49:22.381271+00:00, confidence not recorded.
  - readme: https://github.com/neo4j-contrib/neomodel (fetched 2026-08-28T04:03:32.373599+00:00, sha bb52abf3683b)
  - registry_pypi: https://pypi.org/pypi/neomodel/json (fetched 2026-08-29T12:52:33.683977+00:00, sha f376d24aa358)
- Data as of 2026-08-30T08:39:29.467469+00:00.