Vector Database

Also known as: Vector DB, Embedding Database

In one sentence

A database optimized for storing and searching embeddings (number lists). Finds similar items by comparing their vectors.

A special filing system that stores 'meaning coordinates' and can quickly find things with similar meanings.

Used in RAG systems to store document embeddings and search for relevant chunks. Examples: Pinecone, Weaviate, Chroma, Qdrant.

Learn more about Vector Database in these guides:

Practical examples of vector databases in action: semantic search, chatbot memory, recommendation systems, and more with code snippets.

Deep dive into vector databases. How they work, when to use them, and how to choose the right one for your needs.

Vector databases store and search embeddings efficiently. Learn how they work, when to use them, and popular options.