Graph-vector database in Rust
HelixDB is described as a native graph-vector database built in Rust, combining graph storage and vector search in one system.
HelixDB is a native graph-vector database built in Rust for RAG, semantic search, knowledge graphs, and AI agent workflows. It also publishes cloud and enterprise pricing for its Helix Cloud deployment model.
HelixDB is a native graph-vector database built in Rust. The homepage describes it as an infinitely scalable graph database and positions it for RAG, semantic search, knowledge graphs, and AI agent workflows.
Its cloud architecture, called Helix Cloud, is built on object storage and uses a gateway layer with writer and reader nodes. The site says reader nodes can scale with demand, while the gateway buffers requests so database failures do not immediately surface as errors. Production guidance recommends at least 3 gateways and 3 DB nodes for high availability, while smaller clusters can run in Dev mode for testing.
HelixDB is described as a native graph-vector database built in Rust, combining graph storage and vector search in one system.
The homepage positions HelixDB for RAG, semantic search, knowledge graphs, and AI agent workflows, indicating support for both retrieval and graph-centric applications.
Helix Cloud is built on object storage and is designed to handle any volume of graph and vector data, with reader nodes that scale up under load and scale back down when demand drops.
The site states that production deployments should use at least 3 gateways and 3 DB nodes for high availability, while smaller clusters can run in Dev mode for testing.
The gateway buffers requests so database failures do not cause errors, which the site presents as a robustness feature.
Published pricing covers a usage-based GA Cloud offering on Railway and dedicated arm64 enterprise gateway and database SKUs with hourly billing.
Use HelixDB when you need a database that can support retrieval-augmented generation with both graph relationships and vector similarity in the same application.
Use it for semantic search where embedding-based lookup needs to sit alongside graph structure or relationship traversal.
Use it to model knowledge graphs for applications that need structured entity relationships and scalable storage.
Use it in AI agent workflows where agent-facing graph queries and iterative discovery are part of the application design.
Use the cloud deployment model when you want object-storage-backed infrastructure with reader scaling and published high-availability guidance.
HelixDB is presented as a native graph-vector database built in Rust for RAG, semantic search, knowledge graphs, and AI agent workflows.
The site says Helix Cloud is built on object storage and uses gateways and database nodes. It also notes that smaller clusters can run in Dev mode for testing, while production guidance recommends at least 3 gateways and 3 DB nodes for high availability.
Pricing is published on a pricing.md page. Helix GA Cloud is usage-based on Railway, while enterprise gateway and database SKUs are billed hourly and include additional charges for load balancer/control plane, storage, and egress.
The homepage highlights GitHub, Discord, Docs, Blog, Demo, and Get Started links, and the blog includes tutorials such as Docker deployment, Cursor syntax highlighting, GraphRAG, and MCP guidance.
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