Vendors / Elasticsearch
Elasticsearch
Named in 23 of 50 AI answers across 1 category in September 2026. Best position: Vector databases, 46% answer share, ranked #7, named first in 0%.
46%
Best share Vector databases
What Elasticsearch is
Elasticsearch is a platform from Elastic for people building search and vector database applications, monitoring applications and infrastructure, and protecting against cyber threats. It is available as a hosted, serverless or self-managed product, with resource-based, usage-based and licence-based pricing respectively.
It runs on a distributed search and vector database with an analytics engine. Elasticsearch combines full-text and semantic search to return query results and supports real-time data analysis. RESTful APIs provide access to data, visualisations and deployments.
By category
First edition
| Category | Rank | Answer share | Named first | Models | Δ |
|---|---|---|---|---|---|
| Vector databasesAI infra | #7 of 16 | 0% | GPT-5.6 Sol, ChatGPT, GPT-5.6 Luna, Claude Opus 5, Claude, Claude Fable 5, Gemini, Gemini 3.5 Flash, Perplexity, Sonar Reasoning Pro | new |
What the models said
“If your RAG application relies heavily on structured text filters, exact matches, and semantic search, Elasticsearch's hybrid search is best-in-class.”
“Elasticsearch/OpenSearch and Weaviate are both called out as strongest for hybrid BM25 + vector work pgvector can do hybrid via Postgres full-text search, but it's more assembly required.”
“Elasticsearch / OpenSearch Recommended when hybrid search requirements are primary and you already rely on Elasticsearch for text search.”
“The main contenders right now are pgvector, Pinecone, Qdrant, Weaviate, Milvus, Chroma, and LanceDB, plus platforms like Redis, Elasticsearch, and Vespa.”
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