Dev Breakthroughs
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Druid, Part Deux: Three Principles for Fast, Distributed OLAP

Druid, Part Deux: Three Principles for Fast, Distributed OLAP | Dev Breakthroughs | Scoop.it
From metamarketsgroup.com - May 20, 2011 5:36 PM
Druid’s power resides in providing users fast, arbitrarily deep exploration of large-scale transaction data. Queries over billions of rows, that previously took minutes or hours to run, can now be investigated directly with sub-second response times.

We believe that the performance, scalability, and unification of real-time and historical data that Druid provides could be of broader interest. As such, we plan to open source our code base in the coming year.
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Introducing Druid: Real-Time Analytics at a Billion Rows Per Second

Introducing Druid: Real-Time Analytics at a Billion Rows Per Second | Dev Breakthroughs | Scoop.it
From metamarketsgroup.com - May 1, 2011 12:16 PM
Here at Metamarkets we have developed a web-based analytics console that supports drill-downs and roll-ups of high dimensional data sets – comprising billions of events – in real-time. This is the first of two blog posts introducing Druid, the data store that powers our console. Over the last twelve months, we tried and failed to achieve scale and speed with relational databases (Greenplum, InfoBright, MySQL) and NoSQL offerings (HBase). So instead we did something crazy: we rolled our own database. Druid is the distributed, in-memory OLAP data store that resulted.
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