Asked about Storing and searching vectors
When do you actually need a vector database?
An answer that works
When exact search stops being fast enough, which is usually well past a hundred thousand chunks, or when you need operational features like filtering, replication and incremental updates. Below that, an array and a matrix multiply, or a vector extension on a database you already run, is simpler.
Then they push further
You have 20,000 chunks. What would you use?
Probably the database you already run, such as Postgres with pgvector, or even an in-memory index. At that size exact search is fast enough, and one fewer system to operate matters more.
What would change your mind?
Tens of millions of vectors, strict latency targets under heavy load, filtering or hybrid search the current store handles badly, or a team that already runs a dedicated store well.
What gets marked up
Marked up for starting from existing infrastructure and real numbers. Reaching for a dedicated vector database by default is marked down.
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