Glossary
Vector Database
A database optimised for storing and querying high-dimensional vectors (embeddings) by similarity.
Definition
Vector databases store numerical embeddings of documents, images or audio and provide fast nearest-neighbour search over them. They power semantic search, recommendation and the retrieval step of RAG systems. Options range from purpose-built systems (Pinecone, Weaviate, Qdrant, Milvus) to vector extensions on traditional databases (pgvector on PostgreSQL, Atlas Vector Search on MongoDB).
Why it matters
For most teams, pgvector on a Postgres instance you already operate beats a separate vector DB until scale forces a split. Avoid premature operational complexity.
See also
RAG (Retrieval-Augmented Generation)
AI pattern where an LLM generates answers from documents retrieved at query time, rather than from training data alone.
Read →Embeddings
Dense numerical vector representations of text, images or audio that capture semantic similarity.
Read →PostgreSQL
PostgreSQL engineering — schema design, multi-tenant architecture, performance tuning, migrations and high availability for SaaS and analytical workloads.
Read →Working on Vector Database?
Our AI Developmentteam ships this in production. Tell us your scope and we'll share a written recommendation and fixed quote within 48 hours.
AI Development →