What is Vector Database?

Explained

A vector database stores embeddings and supports fast similarity search. Given a query embedding, it returns the most similar stored vectors. Essential for RAG and semantic search at scale.

Decision guides that use this term

• RAG vs fine-tuning: which one does your enterprise use case need?

Further reading

• Vector Databases for RAG: Powering Semantic Search for LLMs

Related terms

• Embedding Dense numerical representation of text, image, or audio; enables semantic search.
• RAG Retrieve relevant documents and use them as context to generate the answer.
• Semantic Search Search by meaning, not just exact words; uses embeddings.
• Vector Numerical representation; see Embedding.
• Big Data Large volumes of data requiring specialized tools; feedstock for training AI models.
• Context Engineering Designing what the model sees—retrieval, memory, summaries, and window budgeting.