Vector databases explained without the buzzwords
NEO Campus Editorial7 February 20266 min read
A vector database stores embeddings and finds neighbours fast. Whether you need a dedicated one depends on scale and access patterns.
What embeddings are
Numerical fingerprints of meaning. Similar content lives close together in vector space.
When Postgres suffices
Up to a few million vectors, pgvector handles it comfortably. Operational simplicity is a real benefit.
When you need a dedicated store
Hundreds of millions of vectors, hybrid search at scale, or multi-tenant isolation — that is when specialised stores start to earn their keep.
