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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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<br><br>
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Chronix Kassiopeia is a specialized time series package that can easily be added to Chronix.
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It provides a time series implementation and <b>high-level time series functions</b>, e.g., trend
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detection, frequencies, outliers. If Kassiopeia does not fit your needs, you can easily use your custom
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time series within Chronix by implementing a converter with two methods.
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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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but it also shaves off 83% of the access time, and up to 78%
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Apache Solr offers several useful features like scalability, fault tolerance, distributed 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>. Store the time series in a Chronix Storage and HDFS or in a Chronix Server cluster.
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Leverage Apache Spark to process a time series in parallel.
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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>
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</ol>
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<p>
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Chronix is in a very early stage and hence there is a lot of work to do. Anyway! ;-)
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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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