Build 10x Faster with the First Native Graph-Vector Database
Accelerate development with a unified graph and vector database, built in Rust, designed for RAG and AI applications.
Installation
HelixDB is production-ready on Unix and completely open-source. Start writing your queries and deploying code in minutes.
$ curl -sSL "https://install.helix-db.com" | bash $ helix install
Better by Design
Stop juggling multiple databases. HelixDB unifies graph and vector capabilities in a single, powerful database that speeds up your development process.
Simplified Architecture
One database to handle both graph relationships and vector embeddings. No more complex integrations.
Faster Development
Write queries that combine graph traversal and vector similarity in a single operation.
High Performance
Optimised in Rust, HelixDB even compiles queries into your database for speed and simplicity.
Traditional Setup
Graph Databases
Complex setup and maintenance
Vector Databases
Multiple services to manage
Cloud Infrastructure
High operational overhead
Helix Setup
One Simple Solution
Replace your complex stack with a single platform
- • No complex infrastructure to manage
- • No multiple services to maintain
- • No operational overhead
QUERY addUsers() =>
user1 <- AddV<User>({Name: "Alice", Age: 30})
user2 <- AddV<User>({Name: "Bob", Age: 25})
AddE<Follows>::From(user1)::To(user2)
RETURN user1, user2
POST https://api.helix-db.com/project-name/addUsers
→ Returns {
user1: User,
user2: User
}Lightning-Fast Queries
Transform complex database queries into instant API endpoints. Write once, deploy as a blazing-fast microservice.
Simply write your queries and we build them directly into your database, and we'll automatically optimize it at build time. Your query becomes a dedicated API endpoint, eliminating parsing overhead and delivering exceptional performance.
With built-in caching and automatic optimization, you can be sure your queries will run at peak performance every time.
Simple, Powerful, and Intuitive
See how HelixQL simplifies complex queries compared to traditional query languages
HelixQL
QUERY findFriends(userID: String) => user <- V<User>(userID) posts <- user::Out<Posts>::RANGE(20) RETURN user::|usr|{ ID, name, age, following: usr::In<Follows>, posts: posts::{ postID: ID, creatorID: usr::ID, .. }, }MATCH (user:User)WHERE id(user) = $userIDMATCH (user)-[:Posts]->(posts)WITH user, collect(posts)[..20] as postsRETURN user.name as name, user.age as age, id(user) as id, [(follower)-[:Follows]->(user) | follower] as following, [p IN posts | { postID: id(p), creatorID: id(user), title: p.title, createdAt: p.createdAt, content: p.content }] as postsHelixQL
QUERY findFriends(userID: String) => user <- V<User>(userID) posts <- user::Out<Posts>::RANGE(20) RETURN user::|usr|{ ID, name, age, following: usr::In<Follows>, posts: posts::{ postID: ID, creatorID: usr::ID, .. }, }MATCH (user:User)WHERE id(user) = $userIDMATCH (user)-[:Posts]->(posts)WITH user, collect(posts)[..20] as postsRETURN user.name as name, user.age as age, id(user) as id, [(follower)-[:Follows]->(user) | follower] as following, [p IN posts | { postID: id(p), creatorID: id(user), title: p.title, createdAt: p.createdAt, content: p.content }] as posts70% Less Code
Write cleaner, more maintainable queries with our intuitive syntax
Type Safety
Catch errors at compile time with full type checking and IDE support
Native Vector Support
Seamlessly combine graph traversals with vector operations
Use Cases
Discover how Helix can be used in a wide range of use cases.
Code Documentation
Effectively search your documentation from your codebase to help AI agents.
Semantic Search
Find relevant information across your entire database using natural language.
Code Based Indexing
Store the context of your code alongside distinct relationships (such as file structure & dependencies).
Knowledge Base
Create and maintain a searchable knowledge base from your technical documentation.
AI Coding Agents
Retrieve the most relevant code snippets from your codebase to help AI agents.
Vector & Graph RAG
Build traditional Graph or Vector RAG. Utilize vectors and graphs independently.
Hybrid RAG
Combine Vector and Graph RAG to create a more powerful and accurate retrieval system.
Part Lookup
Find the most relevant parts of a product from your database and other compatible parts.
Simple, transparent pricing
Helix prices can be used on demand or reserved. No hidden fees, no surprises.
Small
For independent developers and working on side projects
Medium
For independent developers and small teams
Large
For medium to large teams and organizations
X-Large
For large teams and organizations
Join Our Growing Community
Be part of the next generation of graph database technology. Connect with developers and innovators building the future.
Book a Demo
See how Helix can transform your development workflow. Schedule a personalized demo with our team.