Chronix A fast and efficient time series storage

Why Chronix


Easy to use

Chronix is easy to use and integrated within minutes.



Chronix stores time series highly compressed.



Chronix has very fast query and analysis times.



Chronix has high-level query functions.



Chronix is free to use for everyone and forever.


Chronix natively speaks time series. You can store nearly every kind of data type within a time series due to its flexible design. You decide what a time series looks like. Check out the documentation of Chronix.

Chronix is built to store time series highly compressed and for fast access times. In comparison to related time series databases, Chronix does not only take 5 to 171 times less space, but it also shaves off 83% of the access time, and up to 78% off the runtime on a mix of real world queries. For the measurements we used a commodity hardware laptop computer and Chronix using the Apache Solr scenario (single node).

Chronix supports three different scenarios, pursuing different goals:

  1. Chronix Storage: Use Chronix as a small storage library and plug it into your application. It stores the time series using Apache Lucene.
  2. Chronix Server: Combine Chronix with Apache Solr for a typical client-server scenario. Apache Solr offers several useful features like scalability, fault tolerance, distributed indexing, or replication.
  3. Chronix Spark: Whenever you need a parallel and distributed time series processing, integrate Chronix with Apache Spark. Leverage Apache Spark to process a time series in parallel.

Chronix Stack

The whole Chronix Stack is open source and free to use for everyone without any restrictions. The stack has Chronix at its core but several other open source projects like logstash, collectd, fluentd, Grafana and Zeppelin are tightly integrated.

Chronix Stack


Get up and running with Chronix in 3 minutes with our quickstart guide:


You need Java 8 installed on your system. That's it :-)

Download and Run

The Chronix showcase consists of two parts. Pick the latest releases of the Chronix Server (download) and an example JavaFX application (download) for time series exploration. Unzip the Chronix Server (it contains one week of operational time series data), the JavaFX application is an executable Java archive.
Just use the following instructions:

chronix@chronixDB:~$ mkdir chronixShowcase
chronix@chronixDB:~$ cd chronixShowcase
chronix@chronixDB:~$ wget https://github.com/ChronixDB/chronix.server/releases/download/v0.5-beta/chronix-0.5-beta.zip
chronix@chronixDB:~$ unzip chronix-0.5-beta.zip
chronix@chronixDB:~$ cd chronix-solr-6.4.2/
chronix@chronixDB:~$ chmod +x bin/solr
chronix@chronixDB:~$ export JAVA_HOME=/usr/lib/jvm/java-8-oracle/
chronix@chronixDB:~$ ./bin/solr start
Started Solr server on port 8983 (pid=3591). Happy searching!

Chronix is now running on localhost:8983. Now we can start the JavaFX application. Download the executable jar from GitHub and start it from the console:

chronix@chronixDB:~$ cd chronixShowcase
chronix@chronixDB:~$ wget https://github.com/ChronixDB/chronix.examples/releases/download/v0.5-beta/chronix-timeseries-exploration-0.5-beta.jar
chronix@chronixDB:~$ java -jar chronix-timeseries-exploration-0.5-beta.jar
Setting up Chronix with a remote solr to URL http://localhost:8983/solr/chronix/
Checking connection to solr. Result true.

With the running JavaFX application, you can query Chronix for time series data. For example, a simple query that delivers all time series data whose name contains Load is name:*Load*. Just enter the query term into the text box at the top and hit Shift + Enter to retrieve the result. To compute the maximum, minimum, average of that result you add a filter query metric{max;min;avg} in the second text box and press again Shift + Enter. To check if the average load (name:*Load*avg) has a positive trend you can use metric{trend} in the filter query text box. You start the analysis by pressing Shift + Enter. The queries described and shown in the screencast represent only a few simple queries, check out our examples repository for more details.


If you want to know more about Chronix you can check out our various publications. Below you can find a chronological ordered list with links to the talks, papers, and blog entries.


  • Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in Operational Data, FAST, 2017 Slides Paper Poster


  • Chronix as long term storage for Prometheus, Cloud Native Conference, 2016, Slides Recording
  • Time Series Processing with Solr and Spark, Lucene Revolution, 2016, Slides
  • The new time series kid on the block, Apache Big Data North America, 2016, Slides
  • Time Series Processing with Apache Spark, Apache Big Data North America, 2016, Slides
  • Chronix – A fast and efficient time series storage based on Apache Solr, Open Source Data Center Conference, 2016, Slides


  • Fast and efficient operational time series storage: The missing link in dynamic software analysis, Symposium on Software Performance, 2015, Slides
  • Open Source Project Chronix: An efficient and fast time series database based on Apache Solr, 2015, Blog
  • Apache Solr as a compressed, scalable, and high performance time series database, 2015, Blog
  • Apache Solr as a compressed, scalable and high performance time series database, FOSDEM, 2015, Slides


Check out the release pages for the latest versions of our subprojects:

The ChronixDB account on GitHub contains all sources of all projects and examples.