What is a vector database?
Storage that finds information by meaning rather than by matching words.
Knowledge hub
What is a vector database?
A vector database stores text, images or other data as numerical representations called embeddings, positioned so that similar meanings sit close together. Searching returns the closest matches by meaning rather than by exact keyword, which is what makes retrieval systems work.
Why keyword search is not enough
A user asking 'how do I get my money back' will not match a document titled 'refund policy' on keywords alone. Semantic search finds it, because the two phrases occupy similar positions in meaning-space.
In practice the strongest systems combine both — keyword matching catches exact product codes and names, semantic search catches paraphrase.
Do you need a separate database?
Often not. PostgreSQL with the pgvector extension handles modest volumes perfectly well and avoids running another system. Dedicated vector databases earn their place at large scale or with demanding latency requirements, and we would rather not add infrastructure you do not need.
Talk it through before you commit
A discovery call is a working session on your constraint, not a sales pitch.
Related
Where this connects
Quick inquiry
Tell us what you're trying to build
A short note is enough. You'll hear back from the team, not a bot — usually within one working day.
- +91 83695 17339
- Palava City, Dombivli, Thane, MH 421204