HelixDB

Written from scratch in Rust, HelixDB is a graph-vector database for knowledge graphs and AI memory. The argument is consolidation. Rather than an application database, a vector store, a graph store and glue code between them, agents get federated access to company data from one engine.

The primary data model is graph plus vector, with key-value, document and relational data supported alongside. Queries are authored in a DSL for Rust, TypeScript, Go and Python, all producing the same JSON abstract syntax tree and posted to a running instance over one HTTP query endpoint, with no build or deploy step.

Getting an instance running is the CLI's job.

• Install script: a shell one-liner on macOS and Linux, a PowerShell command on Windows, and an update subcommand afterwards.
• Interactive bootstrap: the chef command scaffolds a project, starts a local instance, seeds example data and installs the query skills and docs server.
• Agent handoff: chef detects Claude Code, OpenAI Codex, OpenCode or Cursor Agent and can hand over a one-line description to build a working app.
• SDK packages: published releases on crates.io, npm, PyPI and the Go module proxy.
• Local defaults: the dev instance listens on port 6969, which is where every SDK example points.

Version names deserve care, since HelixDB v3 is current while the wire endpoint keeps a v2 path meaning something else. A managed cloud runs the same engine on object storage with full ACID transactions, a single writer with auto-scaling readers and high availability, and the CLI authenticates against it.