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VDR.aihelix-db
HelixDB is a Rust-based OLTP database combining graph, vector, and traditional data models, designed for AI applications and RAG systems. It runs locally or on object storage via a managed cloud service, with query SDKs in Rust, TypeScript, Python, and Go.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | HelixDB/helix-db |
| Owner | HelixDB |
| Primary language | Rust |
| License | Apache-2.0 — OSI-approved |
| Stars | 5.6k |
| Forks | 310 |
| Open issues | 11 |
| Latest release | v3.0.8 (2026-07-05) |
| Last updated | 2026-07-05 |
| Source | https://github.com/HelixDB/helix-db |
What helix-db is
OLTP graph-vector database written in Rust, supporting hybrid data models (graph, vector, KV, document, relational). Executes queries via REST API (`POST /v1/query`) using a JSON AST, with DSL builders in multiple languages. Local instances use in-memory or disk storage; Cloud deployments scale across object storage with ACID transactions, read replicas, and high availability.
Get the helix-db source
Clone the repository and explore it locally.
git clone https://github.com/HelixDB/helix-db.gitcd helix-db# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Default local instances are in-memory; use `--disk` flag to persist data across restarts, or plan for Cloud deployment for durability.
- DSL builders (Rust, TypeScript, Python, Go) all produce the same JSON AST; choose based on existing team expertise and deployment runtime compatibility.
- No mention of built-in authentication/authorization in local setup; for production, clarify RBAC and multi-tenant isolation requirements before committing.
- Requires Node.js 20+ for TypeScript SDK and working Rust/Go/Python toolchains for respective SDKs; Docker-based local instances reduce platform friction but add container overhead.
When to avoid it — and what to weigh
- Mature, battle-tested production database required — Project was created in Nov 2024 with v3.0.8 as latest release (Jul 2026 in data). Adoption metrics and long-term stability history are not yet established. Only 11 open issues, but production-grade assurance requires additional real-world deployment evidence.
- Heavy OLAP / analytical workload dominance — HelixDB is explicitly OLTP-focused. If your use case is primarily large-scale columnar analytics, batch ETL, or read-heavy reporting, a data warehouse (Snowflake, BigQuery, DuckDB) is more appropriate.
- No need for vector or graph capabilities — If your application uses only relational or KV data without semantic search or graph traversal, the overhead and complexity of HelixDB's hybrid model is unnecessary; simpler RDBMS or KV stores are more cost-effective.
- Strict vendor independence / no cloud lock-in tolerance — Managed service is tightly integrated via CLI and `helix.toml` authentication. Local deployments are possible, but Cloud is the primary commercial offering, creating some operational coupling.
License & commercial use
Apache License 2.0 (Apache-2.0). This is a permissive OSI-approved license allowing commercial use, modification, and distribution with proper attribution and liability disclaimer.
Apache-2.0 permits commercial use. HelixDB Cloud is the primary commercial offering (managed service on object storage). Local open-source deployments can be used commercially under Apache-2.0 terms. No source code contribution requirements for proprietary applications. Recommend reviewing cloud service terms of service and support SLAs separately from the license.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Strong |
| License clarity | Clear |
| Deployment complexity | Low |
| DEV.co fit | Strong |
| Assessment confidence | High |
Apache-2.0 license does not guarantee security audit or formal assurance. Local in-memory instances have no persistence-layer encryption mentioned. Cloud deployments claim ACID transactions and high availability but details on encryption-at-rest, encryption-in-transit, and audit logging are not provided in the source data. No mention of vulnerability disclosure policy or security update cadence. Assess threat model carefully before storing sensitive data; request security documentation from the team.
Alternatives to consider
Weaviate / Qdrant
Dedicated vector databases with mature production deployments and extensive ML integrations. Use if vector search is primary need; lack native graph database features but excel at semantic search + filtering.
Neo4j
Established graph database with native ACID, clustering, and production SLAs. Use if graph queries are the dominant workload; vector support is newer (Neo4j 5.x) and less tightly integrated than HelixDB.
PostgreSQL + pgvector + PostGIS
Mature RDBMS with vector extension (pgvector) and spatial/graph capabilities via PostGIS. Use if you need a battle-tested, single-engine solution with proven operational tooling and broad ecosystem.
Build on helix-db with DEV.co software developers
Start a local HelixDB instance in seconds with `helix start dev`, or explore managed Cloud deployments. See docs.helix-db.com for quickstart guides and SDK examples.
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helix-db FAQ
Can I use HelixDB locally without cloud?
Do I need to choose between graph and vector storage?
What if I need to write in a language not in the SDK list?
Is there a query builder without SDKs?
Software developers & web developers for hire
Our engineers ship vector databases software for a living. DEV.co provides software development services, web development services, and ongoing support for teams standardizing on tools like helix-db.
Ready to unify your AI data layer?
Start a local HelixDB instance in seconds with `helix start dev`, or explore managed Cloud deployments. See docs.helix-db.com for quickstart guides and SDK examples.