Вышла Helixdb — open-source векторно-графовая база данных для AI-приложений, написанная на Rust. Гибридный подход объединяет преимущества векторных и графовых БД, что особенно полезно для семантического поиска и рекомендательных систем. 🔍💡 Уже можно тестировать на GitHub!
- HelixDB
- an open-source graph-vector database written in Rust built for RAG and AI applications. Homepage | Docs | Discord | X HelixDB is a high-performance graph-vector database designed with a focus on developer experience and performance. Built in Rust and powered by LMDB as its storage engine, it combines the reliability of a proven storage layer with modern features tailored for AI and vector-based applications. We are currently using LMDB via Heed3, a rust wrapper built by the amazing team over at Meilisearch . Key Features Fast & Efficient
- Built for performance we’re currently 1000x faster than Neo4j, 100x faster than TigerGraph and on par with Qdrant for vectors. RAG-First
- Native support for graph and vector data types, making it ideal for RAG (Retrieval Augmented Generation) and AI applications Graph-Vector
- Easiest database for storing relationships between nodes, vectors, or nodes AND vectors. Reliable Storage
- Powered by LMDB (Lightning Memory-Mapped Database) for robust and efficient data persistence ACID Compliant
- Ensures data integrity and consistency Getting Started Helix CLI The Helix CLI tool can be used to check, compile and deploy Helix locally. Install CLI curl -sSL » https://install.helix-db.com » | bash Install Helix helix install Setup helix init —path Write queries Open your newly created .hx files and start writing your schema and queries. Head over to our docs for more information about writing queries QUERY addUser ( name
- String , age
- Integer ) = > user < — AddN < User ( { name
- name , age
- age } ) RETURN user QUERY getUser ( user_name
- String ) = > user < — N < User
- : WHERE ( _
- : { name }
- : EQ ( user_name ) ) RETURN user Check your queries compile before building them into API endpoints (optional) # in ./ helix check Deploy your queries # in ./ helix deploy —local Start calling them using our TypeScript SDK or Python SDK . For example: import HelixDB from «helix-ts» ; // Create a new HelixDB client // The default port is 6969 const client = new HelixDB ( ) ; // Query the database await client . query ( «addUser» , { name
- «John» , age
- 20 } ) ; // Get the created user const user = await client . query ( «getUser» , { user_name
- «John» } ) ; console . log ( user ) ; Other commands: helix instances to see all your local instances. helix stop to stop your local instance with specified id. helix stop —all to stop all your local instances. Roadmap Our current focus areas include: Expanding vector data type capabilities for RAG applications Enhancing the query language with more robust type checking Implementing a test suite to enable end-to-end testing of queries before deployment Building a Deterministic Simulation Testing engine enabling us to robustly iterate faster Binary quantisation for even better performance Long term projects: In-house graph-vector storage engine (to replace LMDB) In-house network protocol & serdes libraries (similar to protobufs/gRPC) License HelixDB is licensed under the The AGPL (Affero General Public License). Commercial Support HelixDB is available as a managed service for selected users, if you’re interested in using Helix’s managed service or want enterprise support, contact us for more information and deployment options.
