From the webpage:
An open-source, distributed, time series, events, and metrics database with no external dependencies.
Everything in InfluxDB is a time series that you can perform standard functions on like min, max, sum, count, mean, median, percentiles, and more.
Scalable metrics that you can collect on any interval, computing rollups on the fly later. Track 100 metrics or 1 million, InfluxDB scales horizontally.
InfluxDB’s data model supports arbitrary event data. Just write in a hash of associated data and count events, uniques, or grouped columns on the fly later.
The overview page gives some greater detail:
When we built Errplane, we wanted the data model to be flexible enough to store events like exceptions along with more traditional metrics like response times and server stats. At the same time we noticed that other companies were also building custom time series APIs on top of a database for analytics and metrics. Depending on the requirements these APIs would be built on top of a regular SQL database, Redis, HBase, or Cassandra.
We thought the community might benefit from the work we’d already done with our scalable backend. We wanted something that had the HTTP API built in that would scale out to billions of metrics or events. We also wanted sometehing that would make it simple to query for downsampled data, percentiles, and other aggregates at scale. Our hope is that once there’s a standard API, the community will be able to build useful tooling around it for data collection, visualization, and analysis.
While phrased as tracking server stats and events, I suspect InfluxDB would be just as happy tracking other types of stats or events.
I don’t know, say like the “I’m alive” messages your cellphone sends to the local towers for instance.
I first saw this in Nat Torkington’s Four short links: 5 November 2013.