Approximate Nearest Neighbor

Also known as: ANN

Approximate nearest neighbor search returns vectors that are very likely to be the closest to a query vector without exhaustively comparing every entry in the index. ANN algorithms sacrifice a small, configurable amount of recall for dramatic speed gains — typically achieving millisecond query latency on billion-scale indexes. HNSW, IVF, and PQ are all ANN techniques. The recall-vs-latency tradeoff is tuned through index construction parameters.