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qdrant vs pgvector remains to be benchmarked for a range of relevant sizes, please drop any if you see them!

the only time we've found pgvector to be preferable to qdrant is when the per-category embeddings are very few. E.g. in cases where filtering is expected to reduce the dataset greatly for each query (>99.9%).

This is when the relational nature of postgres really shines - you can even do in-mem calculations for distance.

Qdrant does this as well, with 100% accuracy. But it's not on small categories, but rather on small segments.

You could put different categories in different shards though, resulting in the same effect.

You can also specify exact=true to do the same on any size, but this can get rather slow when your collection grows.

Disclaimer: I'm part of Qdrant.

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