What Is a Vector Database?
A vector database stores embedding vectors and provides efficient similarity search across millions or billions of vectors. Popular options include Pinecone, Weaviate, ChromaDB, pgvector (PostgreSQL), and Qdrant. They are the storage backbone of RAG systems, recommendation engines, and any AI application that needs to find semantically similar content.
How Do Businesses Choose a Vector Database?
Key selection criteria: scale (how many vectors), latency requirements, filtering capabilities, managed vs. self-hosted, and cost. For many mid-market deployments, pgvector (adding vector capabilities to existing PostgreSQL) is the pragmatic choice — no new infrastructure needed. AffixedAI evaluates vector database options as part of the architecture design phase.