It's used by Metamarkets in production (http://metamarkets.com/); I've seen talks about it at Strata and they're getting really impressive query times on terascale problems.

Shameless plug: if you're interested in fast in-memory analytics and more of the PyData bent, I'm building a system with some similarities to Druid at my company (http://www.datapad.io/) but more focused on optimizing single-node performance (i.e. minimizing EC2 expenses) on medium data (single columns of tables typically fit in memory) than high scalability / real time ingest.

It seems like it's part of Netflix's data pipeline, Suro[1].

[1]:http://techblog.netflix.com/2013/12/announcing-suro-backbone...

Netflix also uses Druid: http://www.slideshare.net/g9yuayon/netflix-druidstrata2013

To begin with, it's a column store, which has all kinds of cool implications for data that repeats itself a lot, such as analytics.

Take a look at this page: http://druid.io/druid.html#whois