HNSW is a key method for approximate nearest neighbor search in high-dimensional vector databases, for example in the context of embeddings from neural networks in large language …

There is a significant leap in complexity from a ‘proximity’ graph to ‘hierarchical navigable small world’ graph. We will describe two fundamental techniques that contributed most heavily to …

Mar 30, 2016 · We present a new approach for the approximate K-nearest neighbor search based on navigable small world graphs with controllable hierarchy (Hierarchical NSW, HNSW).

What is a Hierarchical Navigable Small World? Hierarchical navigable small world (HNSW) is a powerful algorithm used in computer science and information retrieval systems to efficiently …

Jun 16, 2023 · HNSW is based on the same principles as skip list and navigable small world. Its structure represents a multi-layered graph with fewer connections on the top layers and more …

May 26, 2024 · Explore the Hierarchical Navigable Small World (HNSW) algorithm through interactive visualizations and demos, providing an in-depth understanding of its mechanics …

Sep 4, 2024 · One of the most effective algorithms for this purpose is HNSW due to its hierarchical structure, which efficiently finds nearest neighbors in large multi-dimensional …

Jun 10, 2025 · What is a hierarchical navigable small world (HNSW)? Hierarchical navigable small world, or HNSW, is a graph-based ANN algorithm that combines navigable small worlds …

Jun 18, 2025 · Introduced by Yury Malkov and Dmitry Yashunin in 2016, HNSW addresses the critical limitation of existing similarity search methods that struggled to maintain both speed …

Hierarchical Navigable Small World (HNSW) is a graph-based Approximate Nearest Neighbor (ANN) search algorithm that offers high speed and scalability, making it a great fit for RAG …