# Neo4j

Graphs for Everyone

Repository: https://github.com/neo4j/neo4j
Canonical: https://ross.abutalabs.com/products/neo4j
Homepage: http://neo4j.com
Language: Java
License: GPL-3.0
License Family: copyleft
Topics: cypher, graphdb, database, nosql, graph, graph-database, neo4j
Last push: 2026-08-24T16:47:42+00:00
Link (homepage): http://neo4j.com
Link (site_page): https://neo4j.com/docs/graph-data-science/current
Link (site_page): https://neo4j.com/company
Link (site_page): https://neo4j.com/docs
Link (site_page): https://neo4j.com/pricing

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 5042, "days_push": 9, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_readme
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 17141, forks 2687 (observed 2026-08-28T04:11:17.724335+00:00)

## What it is
Neo4j is the leading open-source native graph database, storing and querying connected data as nodes and relationships using the Cypher query language. It includes a Graph Data Science library of graph algorithms and ML models, vector indexes for AI/GraphRAG workloads, and client drivers for many languages.

## Use cases
- store and query highly connected data like social networks or fraud rings
- build a knowledge graph for GraphRAG and AI agents
- run graph algorithms like centrality, community detection, and pathfinding
- power real-time recommendation engines
- model and query supply chain or network topology data
- add vector search and agent memory to LLM applications

## When to choose
- your data is highly relational and requires multi-hop traversals or pattern matching
- you need graph algorithms, graph ML, or GraphRAG capabilities at scale
- you want a mature, well-documented graph database with drivers, tooling, and cloud or self-hosted deployment options

## When to avoid
- your workload is simple tabular data better served by a relational or document database
- you need a permissive license for embedding the enterprise edition in a commercial product (GPL-3.0 / commercial licensing)
- you only need lightweight graph analytics on data stored elsewhere without a dedicated database

## Facets
- artifact type: service
- maturity: stable
- function: database, vector-database, search-engine, data-science, machine-learning, rag, sdk
- domain: databases, graph-processing, data-science, artificial-intelligence, developer-tools
- platform: jvm, cross-platform, cloud, self-hosted, python
- tags: graph-database, cypher, nosql, graphrag, knowledge-graph, graph-algorithms, gpl-3.0, retrieval-augmented-generation, docker, kubernetes

## Member repositories
- neo4j/neo4j (main) score 67
- neo4j/neo4j-python-driver (sdk) score 95

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:17.724335+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 2026-08-29T17:03:29.673992+00:00, confidence not recorded.
  - homepage: http://neo4j.com (fetched 2026-08-29T08:01:35.821546+00:00, sha aba3dd61ec07)
  - site_page: https://neo4j.com/docs/graph-data-science/current (fetched 2026-08-29T08:01:35.835680+00:00, sha 4fa0358a9bdc)
  - site_page: https://neo4j.com/docs (fetched 2026-08-29T08:01:35.830674+00:00, sha 66c0b8cf3558)
  - site_page: https://neo4j.com/company (fetched 2026-08-29T08:01:35.837526+00:00, sha 83b70179efb3)
  - site_page: https://neo4j.com/pricing (fetched 2026-08-29T08:01:35.832924+00:00, sha 26b11ff6359c)
- Data as of 2026-08-30T08:39:29.467469+00:00.