Vector Databases

Vector databases store embeddings and support fast nearest-neighbor search for semantic retrieval.

Core capabilities

• High-speed similarity search.
• Metadata filtering (team, language, date).
• Indexing for large-scale vector data.

Common options

Pinecone, Weaviate, Milvus, Qdrant, pgvector.

Where used

• RAG retrieval layer.
• Recommendation systems.
• Duplicate and anomaly detection.