Elasticsearch
The widely deployed search engine, now with dense vector and hybrid search built in.
Elasticsearch is the long-established search engine, and it now does dense vector search alongside its traditional keyword search, which makes hybrid search, blending both, a native capability.
For organisations already running Elasticsearch for logs or search, it is a way to add retrieval without a new system or new operational skills.
Where it fits
A fit when you already run Elasticsearch and want hybrid keyword-plus-vector search in the system you operate.
Where it does not fit
A heavy system to adopt purely for vector search: a dedicated vector database is leaner if that is all you need.
Alternatives to Elasticsearch
The closest options on the map, and where each fits instead.
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Vespa Search and serving engine
A fit for large-scale search and recommendation where vectors, keywords, and learned ranking must all work together.
Unlike Elasticsearch Open source
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Weaviate Dedicated vector database
A fit when you want hybrid search and the option to let the database handle vectorisation for you.
Unlike Elasticsearch Open sourceMaturity: established
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Qdrant Dedicated vector database
A strong pick when retrieval needs to combine similarity with metadata filtering, or has outgrown an in-database extension.
Unlike Elasticsearch Open sourceMaturity: established
Pairs with
Commonly used alongside it.
