# arangodb/arangodb

🥑 ArangoDB is a native multi-model database with flexible data models for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Repository: https://github.com/arangodb/arangodb
Canonical: https://ross.abutalabs.com/products/arangodb
Homepage: https://www.arangodb.com
Language: C++
License: NOASSERTION
License Family: other
Topics: multi-model, graph-database, document-database, key-value, database, distributed-database, arangodb, nosql, graphdb
Last push: 2026-08-27T00:03:28+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 5425, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 14266, forks 884 (observed 2026-08-28T04:11:06.644095+00:00)

## What it is
ArangoDB is a native multi-model database server written in C++ that unifies graph, document (JSON), key-value, full-text, and vector search in a single engine queried via its SQL-like AQL language. It supports horizontal scaling, replication, high availability, and can be run on-prem, in Docker, in Kubernetes, or as a managed cloud service.

## Use cases
- store and query json documents with a flexible schema
- model and traverse connected data as a graph
- run full-text search and ranking over documents
- store and search vector embeddings for ai applications
- build a multi-model backend without gluing several databases together
- shard and replicate data across a cluster for high availability
- query data with a sql-like language (aql) or javascript extensions

## When to choose
- your workload mixes documents, graphs, key-value, and search in one system
- you need deep multi-level relationship traversals with good performance
- you want one query language (AQL) across multiple data models
- you need horizontal scalability, sharding, and automatic failover
- you want vector and full-text search built into the database for AI/RAG workloads

## When to avoid
- you need strict relational guarantees and complex SQL joins across normalized tables
- you only need a simple key-value cache like Redis
- you depend on a very large ecosystem of third-party tools built around PostgreSQL or MongoDB
- you require a fully permissive open-source license for commercial embedding (Enterprise features are commercial; license is not standard OSI)

## Facets
- artifact type: application
- maturity: stable
- function: database, vector-database, search-engine
- domain: databases, graph-processing, large-language-models, developer-tools
- platform: windows, self-hosted, cloud
- tags: multi-model-database, nosql, aql, graph-database, document-store, key-value-store, full-text-search, vector-search, arangosearch, distributed-database, graph-processing, search, linux, macos, docker, kubernetes

## Member repositories
- arangodb/arangodb (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:06.644095+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 2026-08-29T17:12:41.277882+00:00, confidence not recorded.
  - readme: https://github.com/arangodb/arangodb (fetched 2026-08-28T04:11:06.644095+00:00, sha 9e312ca124c2)
  - homepage: https://www.arangodb.com (fetched 2026-08-29T08:06:23.083421+00:00, sha 5c6a465dafad)
  - site_page: https://docs.arango.ai/ (fetched 2026-08-29T08:06:23.097112+00:00, sha ebaf8c73b5d8)
  - site_page: https://arango.ai/about-us (fetched 2026-08-29T08:06:23.099202+00:00, sha 9f2b69390e5a)
  - site_page: https://docs.arango.ai/contextual-data-platform/install-and-upgrade (fetched 2026-08-29T08:06:23.095041+00:00, sha abcb7f731f49)
  - site_page: https://docs.arango.ai/ecosystem/drivers (fetched 2026-08-29T08:06:23.101187+00:00, sha e2fbb2de6c58)
  - site_page: https://arango.ai/pricing (fetched 2026-08-29T08:06:23.092768+00:00, sha eb3386cf2f40)
- Data as of 2026-08-30T08:39:29.467469+00:00.