RAG Series (6): Vector Databases — Storage and Retrieval Infrastructure

Why Do We Need Specialized Vector Databases? In the first five articles, we figured out how to chunk documents and generate embeddings. Now where do these vectors live, and how are they efficiently retrieved? You might wonder: "Can't I just store vectors in Redis or PostgreSQL?" No — traditional databases are designed for exact queries (e.g., WHERE id = 123 ), while vector retrieval is Approximate Nearest Neighbor (ANN) search : given a query vector, quickly find the Top-K most similar vectors a