by Amit Shekhar · 6 June 2026
How does a Vector Database work?
How a Vector Database works. This is one of the most important pieces behind modern AI search, recommendations, and tools like ChatGPT that answer questions from our own documents.
Read on Outcome School ↗then come back to lock it in
Before you read, guessWhat concept must be understood before exploring vector databases, as vectors originate from it?
Ten seconds, a guess, then read — a wrong guess still makes the answer stick.
What this article covers
- What is a Vector Database?
- A quick recap of embeddings
- Why normal databases fall short
- What a Vector Database actually stores
- How do we measure similarity?
- Cosine similarity
- Dot product
- Euclidean distance
- The nearest neighbour problem
- Why brute force is too slow
- Approximate Nearest Neighbour (ANN) and indexing
- HNSW explained simply
- IVF explained simply
- PQ explained simply
- A small code example
- Real-world applications of Vector Databases
The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.
