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druid/docs/comparisons/druid-vs-elasticsearch.md
Gian Merlino d007477742
Docusaurus build framework + ingestion doc refresh. (#8311) 
* Docusaurus build framework + ingestion doc refresh.

* stick to npm instead of yarn

* fix typos

* restore some _bin

* Adjustments.

* detect and fix redirect anchors

* update anchor lint

* Web-console: remove specific column filters (#8343)

* add clear filter

* update tool kit

* remove usless check

* auto run

* add %

* Fix resource leak (#8337)

* Fix resource leak

* Patch comments

* Enable Spotbugs NP_NONNULL_RETURN_VIOLATION (#8234)

* Fixes from PR review.

* Fix more anchors.

* Preamble nix.

* Fix more anchors, headers

* clean up placeholder page

* add to website lint to travis config

* better broken link checking

* travis fix

* Fixed more broken links

* better redirects

* unfancy catch

* fix LGTM error

* link fixes

* fix md issues

* Addl fixes
2019-08-20 21:48:59 -07:00

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druid-vs-elasticsearch Apache Druid vs Elasticsearch

We are not experts on search systems, if anything is incorrect about our portrayal, please let us know on the mailing list or via some other means.

Elasticsearch is a search system based on Apache Lucene. It provides full text search for schema-free documents and provides access to raw event level data. Elasticsearch is increasingly adding more support for analytics and aggregations. Some members of the community have pointed out the resource requirements for data ingestion and aggregation in Elasticsearch is much higher than those of Druid.

Elasticsearch also does not support data summarization/roll-up at ingestion time, which can compact the data that needs to be stored up to 100x with real-world data sets. This leads to Elasticsearch having greater storage requirements.

Druid focuses on OLAP work flows. Druid is optimized for high performance (fast aggregation and ingestion) at low cost, and supports a wide range of analytic operations. Druid has some basic search support for structured event data, but does not support full text search. Druid also does not support completely unstructured data. Measures must be defined in a Druid schema such that summarization/roll-up can be done.