nyas

A lightweight vector database for similarity search

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// Initialize the vector store
let store = VectorStore::new(config);

// Add embeddings
store.add(vectors, metadata);

// Search for similar vectors
let results = store.search(query, k: 10);

Built for Performance

Multiple Distance Metrics

Support for L2, Cosine, and Dot Product similarity measures for flexible vector comparison.

Hybrid Execution

Intelligent CPU/GPU hybrid execution for optimal performance across different workloads.

Graph-Based Search

Inspired by DiskANN and FreshDiskANN for fast, accurate billion-point nearest neighbor search.

Flexible Storage

Multiple storage backend options to match your infrastructure and performance needs.

Written in Rust

Memory-safe and blazingly fast implementation with zero-cost abstractions.

Apache 2.0 License

Open source and free to use in commercial projects with a permissive license.

Fast

Efficient similarity search

Simple

Easy to integrate

Scalable

Billion-point capable

Simple, Transparent Pricing

Start free. Scale when you're ready. No hidden fees.

Monthly Annual Save 20%

Free

Sandbox

^₹0

/ month · no card required

SQL Queries 1,000 / month
Database Tables Max 5 tables
Vector Search Basic (limited)
Support Community (Discord)

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