| Hi HN, I built EdgeVec, a vector database that runs entirely in the browser. It implements HNSW (Hierarchical Navigable Small World) graphs for approximate nearest neighbor search. Performance:
- Sub-millisecond search at 100k vectors (768 dimensions, k=10)
- 148 KB gzipped bundle
- 3.6x memory reduction with scalar quantization Use cases: browser extensions with semantic search, local-first apps, privacy-preserving RAG. Technical: Written in Rust, compiled to WASM. Uses AVX2 SIMD on native, simd128 on WASM. IndexedDB for browser persistence. npm: https://www.npmjs.com/package/edgevec
GitHub: https://github.com/matte1782/edgevec This is an alpha release. Main limitations: build time not optimized, no delete operations yet. Would love feedback from the community! |