Vector databases

Vector databases store embedding vectors produced by models like OpenAI text-embedding-3-small and support approximate nearest neighbor search. They enable similarity queries that traditional relational indexes cannot perform efficiently at scale.

Codeaxes deploys vector databases when AI products need semantic search, recommendation, or retrieval-augmented generation over unstructured content. Pairing embeddings with metadata filters in PostgreSQL extensions or dedicated stores like Pinecone keeps retrieval fast and relevant.