rvLite

Lightweight npm package providing an embedded vector database for Node.js applications. Offers vector similarity search with HNSW, BM25 full-text search, hybrid search using weighted fusion or Reciprocal Rank Fusion (RRF), multi-namespace support, CRUD operations, metadata filtering, concurrency safety, and persistent storage to disk. Designed for RAG pipelines and semantic search use cases.

A tiny embedding database in pure Rust, implemented as a lightweight Axum server for fast vector search on small to medium datasets. It stores all indexes in memory, enabling vertical scaling to over 100 million vectors with comparable speed and slightly better accuracy than advanced vector databases. Open-source under the MIT license, ideal for simple setups like document chat or website search.

A simple, easy-to-hack vector database library implemented in Rust. It supports fast cosine similarity searches with Rayon parallelism, embedded persistence, and a minimal API ideal for prototyping and educational purposes.

On-device vector database with out-of-the-box data sync, designed for resource-efficiency on mobile, IoT, and embedded devices, enabling offline-first AI applications without internet dependency.

Lightweight embedded vector search engine designed for real-time vector search on edge devices like robots, kiosks, and mobile phones with limited computational resources and offline capabilities.

A high-performance embedded database for edge devices and mobile, offering vector search capabilities for AI applications.