{"slug":"elasticsearch-opensearch","name":"Elasticsearch/OpenSearch","domain":null,"verdict":"As of 2026-07-19, ChatGPT, Claude, Gemini, Grok collectively rank Elasticsearch/OpenSearch #6 of 6 for vector database for production rag. Source: https://modelsagree.com/product/elasticsearch-opensearch (modelsagree.com, CC BY 4.0).","best_rank":6,"categories":1,"entries":[{"slug":"best-vector-database-for-production-rag","title":"Best Vector database for production RAG","rank":6,"of":6,"score":1,"appearances":1,"modelRanks":{"Claude":5},"reason":"Where RAG needs first-class lexical + vector hybrid retrieval (the common production reality), BM25 maturity, aggregations, and battle-tested ops matter more than raw ANN benchmarks; many teams already run it, and int8/BBQ quantization made dense retrieval cost-competitive.","reasons":[{"model":"Claude","reason":"Where RAG needs first-class lexical + vector hybrid retrieval (the common production reality), BM25 maturity, aggregations, and battle-tested ops matter more than raw ANN benchmarks; many teams already run it, and int8/BBQ quantization made dense retrieval cost-competitive."}],"fixes":[{"model":"Claude","fix":"JVM heap management and index tuning demand real operational expertise, and pure vector latency/cost still trails purpose-built engines at equivalent recall."}],"updated":"2026-07-19","api":"https://modelsagree.com/api/v1/best/best-vector-database-for-production-rag.json"}],"page":"https://modelsagree.com/product/elasticsearch-opensearch","check":"https://modelsagree.com/check?q=Elasticsearch%2FOpenSearch","updated":"2026-07-21T00:03:04.167Z","attribution":"modelsagree.com, CC BY 4.0"}