What is a vector database?

What is a vector database?

A vector database is a type of database purpose-built to store and query high-dimensional vector embeddings. Unlike traditional databases that search for exact matches, vector databases find the most similar vectors using distance metrics like cosine similarity or Euclidean distance.

How does vector search work?

Vector databases use specialized indexing algorithms (like HNSW or IVF) to organize vectors in a way that enables fast approximate nearest neighbor (ANN) search. This allows finding the most semantically similar items in milliseconds, even across millions of vectors.

When to use a vector database

Vector databases are essential for AI applications including semantic search, recommendation engines, image similarity search, retrieval-augmented generation (RAG), and anomaly detection.