Understanding Vector Databases for RAG Applications

What is a Vector Database?

Unlike relational databases that store rows and columns, vector databases store data as high-dimensional mathematical vectors (embeddings). This allows you to perform semantic search—finding items that are conceptually similar, rather than just matching keywords.

RAG: Making AI Smarter

Retrieval-Augmented Generation (RAG) is a technique where you search a vector database for relevant information and pass that context to an LLM before asking it a question. This grounds the AI in your specific data and drastically reduces hallucinations.

Popular Options

Tools like Pinecone, Milvus, and PostgreSQL with pgvector have made implementing vector search highly accessible for developers building AI-native applications.