RAG & knowledge

Vector Database

A specialized database that stores and queries high-dimensional vector embeddings at scale.

Vector databases store embeddings and answer 'find me the K most similar vectors to this query vector' in milliseconds — even with billions of vectors. They power RAG, semantic search, and recommendation systems.

Unlike SQL databases that look for exact matches, vector DBs use approximate nearest neighbor (ANN) algorithms — HNSW, IVF, ScaNN — to trade a tiny bit of precision for huge speed gains.

Top vector databases in 2026: Pinecone (managed), Weaviate, Qdrant, Chroma, Milvus, pgvector for Postgres.

Esempio in GlobalChatbot

GlobalChatbot uses Pinecone with per-tenant namespaces — your data is logically isolated from every other customer's, so you never train shared models.

Vedi in azione.

GlobalChatbot — agente AI per aziende serie. Configurazione in 5 minuti, 45 lingue, senza carta richiesta.

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