HNSW vector index: 100K search in 27ms (58x faster than brute-force)
- instant-distance HNSW implementation for approximate nearest neighbors
- HnswStore: build from stored embeddings, in-memory index, thread-safe
- POST /vectors/hnsw/build — build index from Parquet (100K in 35s release)
- POST /vectors/hnsw/search — fast ANN search
- GET /vectors/hnsw/list — list loaded indexes
Benchmark (100K × 768d, release build):
Brute-force: 1,567ms
HNSW: 31ms (50x)
HNSW warm: 27ms (58x)
Build cost: 35s one-time for 100K vectors (release mode)
ef_construction=40, ef_search=50 — good recall/speed balance
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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