hnswlib-node

Overview

hnswlib-node provides Node.js bindings for HNSWlib, enabling approximate nearest-neighbor search based on hierarchical navigable small world graphs in JavaScript and TypeScript applications.

Key Features

• HNSW Algorithm: Fast approximate nearest-neighbor search
• Multiple Distance Metrics: L2 (Euclidean), Cosine, Inner Product
• File Persistence: Save and load indices to/from disk
• Filter Functions: Search with custom filter predicates
• LangChain Integration: Compatible with LangChain vector stores
• Active Development: Regular updates and maintenance

Installation

npm install hnswlib-node

Available on npm: https://www.npmjs.com/package/hnswlib-node

Popularity

• 12,405+ weekly downloads on npm
• Open source under Apache-2.0 License
• Active community and regular updates

Basic Usage

The library provides a simple API for:

• Creating vector indices with specified dimensions
• Adding vectors to the index
• Searching for nearest neighbors
• Persisting indices to files
• Loading indices from disk

Use Cases

• In-Memory Vector Search: Fast vector similarity search for Node.js applications
• Machine Learning: Embedding-based search for ML models
• Recommendation Systems: User/item similarity matching
• Semantic Search: Text embedding similarity in Node.js backends
• RAG Applications: Retrieval component for LangChain-based RAG

Integration

LangChain

Integrated as an in-memory vector store in LangChain JavaScript:

• Fast local vector search
• File-based persistence
• No external dependencies required

Related Projects

• hnswlib-wasm: Browser-based HNSW via WebAssembly
• hnswsqlite: Persistent vector search combining HNSWlib with SQLite

Performance

HNSW algorithm provides:

• Logarithmic search complexity
• High recall rates (90%+ typical)
• Fast query times for approximate search
• Efficient memory usage

API Documentation

Complete API documentation available at: https://yoshoku.github.io/hnswlib-node/doc/

Advantages

• No External Services: Runs entirely in Node.js process
• Simple Setup: Easy npm install, no database server needed
• File Persistence: Indices can be saved and loaded
• Type Safety: Works well with TypeScript
• Small Footprint: Minimal dependencies

Limitations

• In-memory only (until persisted to disk)
• Not suitable for distributed deployments
• Limited to single-machine scale
• No built-in replication or clustering

Pricing

Free and open-source under the Apache 2.0 license.