HNSW vs IVF vs LSH Explained (ANSWERED)
Core ANN index families — graph-based HNSW, inverted-file IVF, and locality-sensitive hashing LSH — with recall, build cost, and memory trade-offs.
TL;DR — Quick Answer
HNSW builds a multi-layer navigable small-world graph for high recall and low query latency at moderate memory cost. IVF partitions vectors into clusters and searches only nearby lists — faster builds, tunable speed/recall via nprobe. LSH uses hash buckets for sublinear search but often lower recall in high dimensions. Most production RAG stacks default to HNSW or IVF variants.
The Interview Question
Compare HNSW, IVF, and LSH indexing algorithms for vector search. What are the trade-offs?
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