From the website:
OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase. OpenTSDB was written to address a common need: store, index and serve metrics collected from computer systems (network gear, operating systems, applications) at a large scale, and make this data easily accessible and graphable.
Thanks to HBase’s scalability, OpenTSDB allows you to collect many thousands of metrics from thousands of hosts and applications, at a high rate (every few seconds). OpenTSDB will never delete or downsample data and can easily store billions of data points. As a matter of fact, StumbleUpon uses it to keep track of hundred of thousands of time series and collects over 100 million data points per day in their main production cluster.
Imagine having the ability to quickly plot a graph showing the number of active worker threads in your web servers, the number of threads used by your database, and correlate this with your service’s latency (example below). OpenTSDB makes generating such graphs on the fly a trivial operation, while manipulating millions of data point for very fine grained, real-time monitoring.
Imagine how a busy sysadmin would react if those metrics were endowed with subject identity and participated in associations with system documentation.
Or metrics of a power distribution center had subject identity so they could tie into multiple emergency/maintenance networks?
Subjects are cheap, subject identity is useful.
(maybe I should make that my tag line, comments?)
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I first saw this at OpenTSDB: A HBase Scalable Time Series Database by Alex Popescu