Prometheus has become an open-source standard in collecting and monitoring metrics, giving software developer teams greater clarity on complex IT operations. And while Prometheus has its own time-series storage subsystem specifically for metrics monitoring, a time-series database like TimescaleDB allows you to ask more complex questions of your data.
In this talk, Ajay will describe TimescaleDB and its use as a somewhat heretical backend for Prometheus. Engineered up from PostgreSQL, TimescaleDB is the only relational, row-oriented time-series database available that supports both full SQL (e.g., JOINs, window functions) and specialized time-centric functions. For our own internal monitoring needs we hoped to use Prometheus, but realized it lacked a proper SQL storage backend. So, we set to work on natively supporting a Prometheus data type.
Mat will demonstrate this data type, which allows for the storage of data in Prometheus' format to be transparently stored in relational format in TimescaleDB for the user. Ultimately, your relational metadata and time-series metrics are then fully available to be indexed and queried using SQL, while the most recent metrics are monitored through the full functionality of Prometheus. We then show how these metrics are beautifully visualized using Grafana.
About Ajay: Ajayis the CEO and Co-founder of TimescaleDB, an open-source time-series database packaged as an extension of PostgreSQL. Ajay's previous startup, communication data analysis company Sensobi, was acquired in 2011 by GroupMe/Skype/Microsoft. Ajay led the mobile team at GroupMe, which grew to millions of daily users and billions of monthly messages over a short period of time. His past experience includes roles at Microsoft, Citigroup, and several startups. He holds Bachelors, Masters degrees from MIT in Computer Science, and an MBA from the MIT Sloan School of Management.
About Mat: Mat has been working on data infrastructure in both academia (Princeton, PhD) and industry. As one of TimescaleDB's core architects he works on performance, scalability, and query power. Previously, he attended Stuyvesant, The Cooper Union, and Princeton.