Vector Database

Definitions

1. A database optimized for storing and querying high-dimensional vectors (embeddings). Uses approximate nearest neighbor (ANN) algorithms like HNSW or IVF to find similar vectors efficiently. Powers semantic search, RAG, and recommendation systems. Examples: Pinecone, Weaviate, Qdrant, Milvus, and pgvector for PostgreSQL.

   In plain English: A specialized database for finding things by meaning (similarity) rather than exact keyword matching.

   Example: "Store document embeddings in Pinecone, then query with the user's question embedding to find the most semantically similar docs for RAG."

Related Terms

• Vector Database
• Retrieval-Augmented Generation
• Semantic Search
• Approximate Nearest Neighbor
• Beam Search
• CLIP
• Contrastive Learning
• Contrastive Loss
• Dense Retrieval
• Dual Encoder
• ELMo
• Knowledge Graph Embedding
• Learning to Rank
• Matryoshka Embeddings
• CLIP Model
• Neural Search