From the webpage:
KairosDB is a fast distributed scalable time series database written primarily for Cassandra but works with HBase as well.
It is a rewrite of the original OpenTSDB project started at Stumble Upon. Many thanks go out to the original authors for laying the groundwork and direction for this great product. See a list of changes here.
Because it is written on top of Cassandra (or HBase) it is very fast and scalable. With a single node we are able to capture 40,000 points of data per second.
Why do you need a time series database? The quick answer is so you can be data driven in your IT decisions. With KairosDB you can use it to track the number of hits on your web server and compare that with the load average on your MySQL database.
KairosDB stores metrics. Each metric consists of a name, data points (measurements), and tags. Tags are used to classify the metric.
Metrics can be submitted to KairosDB via telnet protocol or a REST API.
Metrics can be queried using a REST API. Aggregators can be used to manipulate the data as it is returned. This allows downsampling, summing, averaging, etc.
Do be aware that values must be either longs or doubles.
If your data can be mapped into metric space, KairosDB may be quite useful.
The intersection of time series data with non-metric data or events awaits a different solution.
I first saw this at Alex Popescu’s Kairosdb – Fast Scalable Time Series Database.