Vector Database Basics: HNSW

Vector databases are essential tools for storing and searching through vast amounts of data, where vectors act as points on a map with unique locations. HNSW (hierarchical navigable small world) indexes enable fast approximate nearest-neighbor searches for high-dimensional vector data by efficiently finding similar vectors without scanning the entire dataset. Pgvector is an extension for PostgreSQL that supports HNSW indexes, making it suitable for applications in AI and machine learning where rapid retrieval of information based on vector similarity is crucial. However, HNSW's memory-intensive nature can be a hurdle for developers working with large datasets, which is where pgvectorscale stands out by delivering high performance without consuming much disk space or memory.