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. observed · 2026-08-28
Health v2 · maintenance only
77/100
- Activity 99
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 5425
- days_rel: n/a
- days_push: 7
- n_releases_24m: 0
Adoption not part of the score
14266 stars · 884 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
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
application · maturity stable
database vector-database search-engine databases graph-processing large-language-models developer-tools windows self-hosted cloud 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
7 sources
- readme: https://github.com/arangodb/arangodb · fetched 2026-08-28 · 9e312ca124c2
- homepage: https://www.arangodb.com · fetched 2026-08-29 · 5c6a465dafad
- site_page: https://docs.arango.ai/ · fetched 2026-08-29 · ebaf8c73b5d8
- site_page: https://arango.ai/about-us · fetched 2026-08-29 · 9f2b69390e5a
- site_page: https://docs.arango.ai/contextual-data-platform/install-and-upgrade · fetched 2026-08-29 · abcb7f731f49
- site_page: https://docs.arango.ai/ecosystem/drivers · fetched 2026-08-29 · e2fbb2de6c58
- site_page: https://arango.ai/pricing · fetched 2026-08-29 · eb3386cf2f40
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| arangodb/arangodb | main | 77 |
For agents
markdown · JSON · MCP: product_card(name="arangodb/arangodb")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem