Azure AI Search
hard vector quotas that catch teams mid-project
strong hybrid and semantic ranking, undermined by a hard per-partition vector quota well below total storage that teams routinely discover late.
the capability is solid — good hybrid search, a semantic ranker, and deep integration with the rest of the azure ai stack, where it now underpins microsoft's managed knowledge layer for agents.
the thing that belongs at the top of any review is the quota structure. vector index size is capped per partition at roughly thirty percent of total index storage — five gigabytes on basic, thirty-five on the first standard tier — and microsoft's documentation is explicit that this is a hard limit and that further indexing attempts once exceeded result in failure. teams size the service on total storage and hit a wall at a third of it. there are also caps of 4,096 dimensions per field and ten vector fields per query.
the description above is ours, condensed from the ranking. pricing moves — check it on the vendor's own page before you rely on it.
- category
- vector databases
- pricing
- tier-based hourly pricing; usd rates could not be verified
- website
- azure.microsoft.com
strong hybrid and semantic ranking, undermined by a hard per-partition vector quota well below total storage that teams routinely discover late.
we researched this category against vendors' own pricing pages and licence files. that is where this line comes from — not from the vendor, and not from anything they paid for.