Beringei is Facebook’s open source, in-memory time series database. Justin Teller, Engineering Manager at Facebook, presented the session. According to Justin, large-scale monitoring systems cannot handle large-scale analysis in real time because the query performance is too slow. After evaluating and rejecting several disk-based and existing in-memory cache solutions, Facebook turned their attention to writing their own in-memory TSDB to power the health and performance monitoring system at Facebook. They presented “Gorilla: A Fast, Scalable, In-Memory Time Series Database (http://www.vldb.org/pvldb/vol8/p1816-teller.pdf)” at VLDB 2015.
In December 2016, they open sourced the majority of that work with Beringei (https://github.com/facebookincubator/beringei). In this talk, Justin started by presenting how Facebook uses this database to serve production monitoring workloads at Facebook, with an overview of how they use it as the basis for a disaster-ready, high-performance distributed system. He closed by presenting some new performance analysis comparing (favorably) Beringei to Prometheus. Prometheus is an open source TSDB whose time series compression was inspired by the Gorilla VLDB paper and has similar compression behavior.
After the talk, Justin was kind enough to speak briefly with me. Check it out: https://youtu.be/vi47ZF159PU
It’s been a great conference, and we’re looking forward to seeing you all at Percona Live Europe!
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