Understanding Hierarchical Navigable Small Worlds (HNSW) for Vector Search

This post provides a detailed explanation of the Hierarchical Navigable Small Worlds (HNSW) algorithm, a key indexing strategy for vector databases. It covers the underlying Navigable Small Worlds (NSW) concept, the construction and search processes for both NSW and HNSW, and the hierarchical modifications that improve search efficiency and convergence. The post emphasizes HNSW's role in enabling efficient similarity search for large-scale vector datasets and links to a pedagogical Python implementation.