Approximate Nearest Neighbor Search

Approximate nearest neighbor search is used to search efficiently across millions or billions of embeddings. Since finding the exact nearest neighbor can be computationally expensive, ANN methods return very close matches at much lower cost. This approach forms the performance foundation of modern vector databases. It requires careful engineering trade-offs between retrieval quality and latency.