Evgeny Potapov (ITSumma) delivers the talk, "Storing Time Series in 2019: Modern Database Performance, Scalability, and Reliability Comparison", on DAY 2 of the Percona Live Open Source Database Conference 2019, 5/30, at Austin, TX.

At ITSumma, we provide 24/7 site reliability engineering for more than 300 clients with 10,000+ servers in total, collecting over 200 thousand metrics per second.

In 2010, we realized that existing monitoring systems could not handle our requirements. What we needed was the capability to instantly process and display analytics, store a minimum of 1 year's worth of data in 15-second, (better yet 1-second) intervals, and make quick-fire (as little as 200-millisecond) queries to retrieve high-resolution data snapshots.

That's why we developed our own monitoring system, and it worked well with the infrastructure of that time. In 2018, our system could no longer meet the requirements of new infrastructures, and had outlived its usefulness in some ways.

Since late 2018, we have been developing a new monitoring system.

To assist us with this project, we compared several major solutions for storing time-series data, including Prometheus storage, InfluxDB, Cassandra, Clickhouse and others.

We investigated their capabilities with our production data in terms of performance, stability, scalability, and storage usage.

At Percona Live I would like to present our findings and show the results of our production and performance tests which we consider useful for anyone interested in storing massive amounts of time series data.


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