Vector databases matter when retrieval quality matters. They are not always needed, but they help when search is part of the core product experience.
Good reasons to use one
Use a vector database when your workflow needs semantic search, embeddings, or similarity-based matching across a large corpus.
Use them when you want search to feel fast, flexible, and driven by meaning instead of keywords alone.
- Measure retrieval quality.
- Do not add retrieval infrastructure just because it sounds modern.
How to choose
Pick the managed service when you want the easiest operational path. Pick open-source or self-hosted options when control and customization matter more.
Most teams benefit from a simple baseline before moving to more specialized tuning.
If retrieval is not central to the product experience, a vector database may be too much infrastructure too early.