Embeddings turn meaning into vectors (last post). But if you have a million of them, how do you find the right ones for a query β fast? That's what a vector database does, and it's the retrieval engine behind every RAG app.
Source: [Dev.to](https://dev.to/dev48v/vector-databases-search-by-meaning-at-scale-2mfn)