Vector Database

A vector database stores embedding vectors (numerical representations of text, images, or other data) and enables fast similarity search. When you search for "how to deploy a React app," the vector database finds documents whose embeddings are closest to your query's embedding, even if they use different words.

Vector databases are essential infrastructure for RAG systems, semantic search, and recommendation engines. Products like Pinecone, Weaviate, Chroma, and pgvector enable AI applications to search through millions of documents instantly. If you are building an AI application that needs to search or retrieve information, you will likely use a vector database.

Pinecone: What is a vector database? - https://www.pinecone.io/learn/vector-database/

Chroma: Open-source vector database - https://www.trychroma.com/