nyas

A lightweight vector database for similarity search

// 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