I think the move towards vector databases might be more hype than necessity. Traditional databases, when properly optimized, can handle vector data for many use cases. The push for specialized vector databases could be re-evaluated in terms of efficiency and cost-effectiveness compared to optimizing existing scalar databases.
Well you could store numbers all fine, but indexing vectors for similarity queries seems fairly recent and not all that widespread in the transactional world.
As the traditional db move forward in the space the need for dedicated vector databases will likely shrink, except for some very specific implementation that offer unique enough features (I.e. deeplake does vector search over object storage, which is very convenient for certain specific scenarios)
sqlite has r-trees for instance [0]. Could it be good enough for most use cases? If it's to query a knowledge base for instance, a couple dimensions should be sufficient. With the added benefit of being able to query your data in other ways.
Here is a SQLite extension that uses Faiss under the hood.
https://github.com/asg017/sqlite-vss
Not associated with the project, just love SQLite and find it very useful.