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 <h1 id="apache-druid-incubating-vs-elasticsearch">Apache Druid (incubating) vs Elasticsearch</h1>

 <p>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.</p>

 <p>Elasticsearch is a search systems 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.
 <a href="https://groups.google.com/forum/#!msg/druid-development/nlpwTHNclj8/sOuWlKOzPpYJ">Some members of the community</a> have pointed out<br>
 the resource requirements for data ingestion and aggregation in Elasticsearch is much higher than those of Druid.</p>

 <p>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.</p>

 <p>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.</p>

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	<h1 id="apache-druid-incubating-vs-elasticsearch">Apache Druid (incubating) vs Elasticsearch</h1>

	<p>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.</p>

	<p>Elasticsearch is a search systems 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.
	<a href="https://groups.google.com/forum/#!msg/druid-development/nlpwTHNclj8/sOuWlKOzPpYJ">Some members of the community</a> have pointed out<br>
	the resource requirements for data ingestion and aggregation in Elasticsearch is much higher than those of Druid.</p>

	<p>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.</p>

	<p>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.</p>

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