HelixDB
by HelixDB · Graph-vector database for AI memory, RAG and knowledge graphs
65.3 — BenchRank score out of 100
Screenshots of HelixDB
Homepage
Overview
HelixDB combines knowledge graphs, vector search, temporal data and full-text search in a single Rust engine, aimed at agent memory, RAG and company knowledge bases. Helix Cloud runs it on object storage, with a gateway in front of one writer node and multiple cached reader nodes that scale with load.
- Best for
- Teams building agent memory, GraphRAG or company-wide knowledge search on one graph-vector store.
- Pricing
- The captured text shows no prices; the homepage only points to a separate pricing.md page.
- Runs on
- WebCLI
Strengths and trade-offs
Strengths
- Graph, vector, temporal and full-text search in one Rust engine
- Type-safe traversals from Rust, Go, TypeScript and Python
- Reader nodes scale up under load and back down when demand drops
- Cloud deployment stores graph and vector data on object storage
Trade-offs
- Production high availability needs at least 3 gateways and 3 DB nodes
- Smaller clusters run in Dev mode and are not recommended for production
- No prices on the homepage; pricing sits on a separate pricing.md page
How this score is made up
Each dimension is scored out of 100 and combined into the headline score using fixed weights.
- MCP support
- 80 out of 100
- API quality
- 15 out of 100
- Documentation
- 80 out of 100
- Agent friendliness
- 91 out of 100
- Changelog
- 100 out of 100
- Marketing site structure
- 60 out of 100
- Operational trust
- 40 out of 100
Measured, but not part of the score
Useful to know, but not a mark for or against the product — so these do not affect the ranking.
- Openness
- 85 out of 100
- Maintenance
- 90 out of 100
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