HelixDB/helix-db
HelixDB is an OLTP graph database with native vector and full-text search built in Rust on Object Storage.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest today, with 35 contributors on GitHub.
Gained 66% fewer stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- Provides an OLTP graph database with native vector and full-text search capabilities built in Rust on object storage.
- Combines graph, vector, and full-text search in a single platform to simplify AI application data management without multiple storage layers.
- Use for building AI applications that require integrated graph and vector data models with low-latency querying.
- Use for implementing retrieval-augmented generation (RAG) systems leveraging built-in vector and keyword search.
- Use for creating secure, logically isolated knowledge graphs with embedded data vectorization and agent-friendly query tools.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
HelixDB: a database built from scratch to be the storage backend for any AI application.
HelixDB was built on the thesis that current database infrastructure is built for how humans think about data, not AI. So we've built a database that makes it easy to build all the components needed for an AI application in a single platform.
You no longer need a separate application DB, vector DB, graph DB, or application layers to manage the multiple storage locations. All you need to build any application that uses AI, agents or RAG, is a single HelixDB cluster and HelixQL; we take care of the rest.
HelixDB primarily operates with a graph + vector data model, but it can also support support KV, documents, and relational data.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+538 stars over 84 days across 10 snapshot days; best day +107 on Sep 22.
Forks
395+72
Open issues
22+14
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| D4Vinci/Scrapling | 98.1K | +6.9K | 65 | 1 day ago |
| Leonxlnx/taste-skill | 110.7K | +5.2K | 55 | 1 day ago |
| calesthio/OpenMontage | 77.2K | +4.2K | 40 | — |
| heygen-com/hyperframes | 79.6K | +4.1K | 45 | today |
| HelixDB/helix-db | 6.3K | — | 40 | today |
| Category median | 98.1K | +5.2K | 45 | — |
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