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This repository was archived by the owner on May 6, 2022. It is now read-only.
Copy file name to clipboardExpand all lines: _includes/documentation.html
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@@ -17,7 +17,8 @@ <h2>About</h2>
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<br><br>
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Chronix is built to store time series highly compressed and for fast access times.
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In comparison to related time series databases, Chronix does not only take 5 to 171 times less space,
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In comparison to related time series databases, Chronix does not only take 5 to 171 times less
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space,
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but it also shaves off 83% of the access time, and up to 78%
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off the runtime on a mix of real world queries.
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For the measurements we used a commodity hardware laptop computer and Chronix using the Apache Solr
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Chronix supports three different scenarios, pursuing different goals:
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</p>
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<ol>
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<li><ahref="https://github.com/ChronixDB/chronix.storage/">Chronix Storage:</a> Use Chronix as a small storage library and plug it into your
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application. It stores the time series using <ahref="https://lucene.apache.org/core/">Apache Lucene</a>.
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<li><ahref="https://github.com/ChronixDB/chronix.storage/">Chronix Storage:</a> Use Chronix as a
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small storage library and plug it into your
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application. It stores the time series using <ahref="https://lucene.apache.org/core/">Apache
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Lucene</a>.
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</li>
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<li><ahref="https://github.com/ChronixDB/chronix.server/">Chronix Server:</a> Combine Chronix with <ahref="https://lucene.apache.org/solr/">Apache Solr</a> for a typical client-server scenario.
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Apache Solr offers several useful features like scalability, fault tolerance, distributed indexing, or replication.
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<li><ahref="https://github.com/ChronixDB/chronix.server/">Chronix Server:</a> Combine Chronix with
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<ahref="https://lucene.apache.org/solr/">Apache Solr</a> for a typical client-server scenario.
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Apache Solr offers several useful features like scalability, fault tolerance, distributed
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indexing, or replication.
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</li>
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<li><ahref="https://github.com/ChronixDB/chronix.spark/">Chronix Spark:</a> Whenever you need a parallel and distributed time series processing,
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integrate Chronix with <ahref="http://spark.apache.org/">Apache Spark</a>. Leverage Apache Spark to process a time series in parallel.
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<li><ahref="https://github.com/ChronixDB/chronix.spark/">Chronix Spark:</a> Whenever you need a
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parallel and distributed time series processing,
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integrate Chronix with <ahref="http://spark.apache.org/">Apache Spark</a>. Leverage Apache
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Spark to process a time series in parallel.
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</li>
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</ol>
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<p>
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We have several presentations and papers that describe the architecture and the main concepts of
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Chronix.
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You will find the slides from the <ahref="https://archive.fosdem.org/2015/schedule/event/apache_solr_as_a_compressed,_scalable_and_high_performance_time_series_database/">FOSDEM 2015</a> conference below. For more information about Chronix
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