Vector Database
Definition
A database optimised for storage and search of high-dimensional vectors (embeddings). Core function: fast approximate nearest-neighbour search to retrieve semantically similar content. 2026 representatives: specialised engines (Qdrant, Weaviate, Milvus) and vector extensions of relational or document-oriented databases (e.g. pgvector for PostgreSQL).
Noise — Signal
Vector databases are presented in RAG marketing as "the missing component". In fact the database is the technically least critical element in a RAG pipeline — the levers sit in chunking strategy, embedding model, hybrid search (vector plus keyword), re-ranking and source-rights management. A poorly designed pipeline on a state-of-the-art vector database delivers worse results than a cleanly built pipeline on PostgreSQL with pgvector.
The right question
Not: "Which vector database do we need?" But: "What requirements do we have on volume, latency, filtering, hybrid search and multi-tenancy, and in which order do we optimise chunking, embedding and re-ranking before the choice of database becomes the bottleneck at all?"