[SEJeff]

It isn't a small footprint, but Druid is the best of breed yet most often underrated tool in this space. Influx gets the press because of the simplicity in setting it up, but epic failed at clustering by trying to invent their own multi-raft magic. If you're not analyzing a lot of data Druid doesn't make sense to setup but if you do, it is simply incredible. I can do analytics on 5+ dimensions with 10 billion datapoints quick enough to make it very responsive in grafana. Their most recent release looks quite interesting as well.

https://groups.google.com/forum/m/#!topic/druid-user/nqqb5RI...

[Millenis]

The document (pdf download) specifically mentions Druid in a comparison table.

[raarts]

Citation for the epic fail?

[SEJeff]

They re-did it a few times from scratch, then decided it was hard, and made it a commercial only feature. It still isn't stable. Also, even with their previous clustering, each influx node had to have the entire dataset, so you're limited by the size of data that fits on a single node.

Druid was built from the ground up to be distributed. It means there is some work to set it up, but once you do, it scales horizontally very easily. Bonus points if you run it on something like mesos making it quite easy to deal with (we do).

https://influxdata.com/blog/update-on-influxdb-clustering-hi...

https://influxdata.com/blog/influxdb-clustering-design-neith...

http://www.refactorium.com/distributed_systems/InfluxDB-and-...

etc. They redid their clustering a few times and the 3rd time around made it closed source. Note that $employer also sues influx for data that we are ok with losing ie: metrics. If the data has a low amount of dimensions, influx is faster than druids. However, if you have 3+ dimensions, druid spanks the pants off of influx by nature of distributing the computation better.