September 20, 2026 · 8 min read

What Is a Vector Database

A relational database finds a row by matching it exactly. That breaks the moment the match is about meaning, because a refund article and a customer asking to get their money back share almost no words. A vector database closes that gap. It stores each document as an embedding, a list of numbers that places its meaning at a point in space, and answers a query by returning the records whose points sit closest, measured by cosine similarity, Euclidean distance, or dot product. To stay fast across billions of vectors it searches for the approximate nearest neighbor rather than the exact one, most often through the hierarchical navigable small world graph introduced by Malkov and Yashunin in 2016. This is the infrastructure under retrieval augmented generation and agent memory, and for most teams in 2026 pgvector on the Postgres they already run is the honest place to start.