It depends on scale. If you're storing a small number of embeddings (hundreds of thousands, millions) and don't have complicated filters, then absolutely the convenience factor of pgvector will win out. Beyond that, you'll need something more powerful. I do think the dedicated vector stores serve a useful place in the market in that they're extremely "managed" - it is really really easy to just call an API and never worry about pre- or post- filtering or sharding your index across a large cluster. But they also have weaknesses in that they're usually optimized around small(er) scale where the bulk of their customers lie, and they don't really replace an actual search system like ElasticSearch.