Danny Yuan, Cloud System Architect at Netflix, and I recently co-presented at the Strata Conference in Santa Clara. The presentation discussed how Netflix engineers leverage Druid, Metamarkets’ open-source, distributed, real-time, analytical data store, to ingest 150,000 events per second (billions per day), equating to about 500MB/s of data at peak (terabytes per hour) while still maintaining real-time, exploratory querying capabilities. Before and after ...

Introduction Before jumping straight into why Metamarkets open sourced Druid, I thought I would give a brief dive into what Druid is and how it came about. For more details, check out the Druid white paper. We are lucky to be developing software in a period of extreme innovation. Fifteen years ago, if a developer or ops person went into his or her boss's office ...

15 Minutes to Live Druid Big Data reflects today’s world where data generating events are measured in the billions and business decisions based on insight derived from this data is measured in seconds. There are few tools that provide deep insight into both live and stationary data as business events are occurring; Druid was designed specifically to serve this purpose. ...

  In April 2011, we introduced Druid, our distributed, real-time data store. Today I am extremely proud to announce that we are releasing the Druid data store to the community as an open source project. To mark this special occasion, I wanted to recap why we built Druid, and why we believe there is broader utility for Druid beyond Metamarkets’ ...

The Metamarkets solution allows for arbitrary exploration of massive data sets. Powered by Druid, our in-house distributed data store and processor, users can filter time series and top list queries based on Boolean expressions of dimension values. Given that some of our dataset dimensions contain millions of unique values, the subset of things that may match a particular filter expression ...