A vector database stores high-dimensional embeddings and answers similarity queries — "find me the 20 items closest to this vector" — in milliseconds, even across billions of records. It is the workhorse of any production RAG or semantic search system.
Leading options in 2026: Pinecone (managed, dominant enterprise choice), Weaviate (open source with hybrid keyword + vector search), pgvector (Postgres extension — great when you already run Postgres), Milvus (open source at scale), Qdrant (Rust-based, fast), and Chroma (embedded, developer-friendly).
Selection factors: latency, filter support, hybrid search, scale, hosting model, and cost. Nagro Solutions has shipped RAG systems on Pinecone, pgvector, and Weaviate — the choice always depends on the client's existing infrastructure and scale.