nnethercott/hannoy
Production-ready KV-backed HNSW implementation in Rust using LMDB
Supports multiple distance metrics (euclidean, cosine, manhattan, hamming) with quantized variants, and offers Python bindings via PyO3 for integration beyond Rust. The implementation uses compressed bitmaps for graph edges (~200 bytes per vector overhead) and enables dynamic insertions/deletions without full re-indexing, while optional memory-mapping prefetching via `madvise` reduces cold-start latencies by several milliseconds.
71 stars and 46,404 monthly downloads. Available on PyPI.
Stars
71
Forks
9
Language
Rust
License
MIT
Category
Last pushed
Mar 05, 2026
Monthly downloads
46,404
Commits (30d)
0
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