Elasticsearch
the licence objection to using it for vectors is largely obsolete
best-in-class hybrid retrieval with transparent serverless pricing — and its dense and sparse vector code sits in the agpl-licensed tree, not the restricted one.
the widespread belief that elasticsearch vector search requires a commercial licence is wrong, and it is worth stating plainly because it has steered a lot of teams away. the dense and sparse vector field mappers live in the main server tree, which carries the triple licence including agplv3. they are not in the elastic-licensed extension tree. the learned-sparse elser model is a separate matter and is restricted, but ordinary vector search is not.
on capability it is close to the top of the category for hybrid. real bm25, reciprocal rank fusion, mature filtering and aggregations — this is a full search engine rather than a vector store with keyword search bolted on. its better binary quantization work has been strong.
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
- serverless from $0.09 per search VCU-hour; storage $0.047/GB/month
- website
- elastic.co
best-in-class hybrid retrieval with transparent serverless pricing — and its dense and sparse vector code sits in the agpl-licensed tree, not the restricted one.
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.
more vector databases
pgvector
we checked thisfree — PostgreSQL Licensethe correct default for most teams, and it quietly got good
Qdrant
we checked thisfree tier; cloud billed hourly on compute and storagefiltering built into the graph traversal, not bolted around it