Today, we are extremely excited and proud to announce the general availability (GA) of Apache Drill 1.0, as part of the MapR Distribution. Congratulations to the Drill community on this significant milestone and achievement!

Incubated in September 2012 as an Apache project, Drill started with an ambitious goal to provide a low-latency SQL engine for the modern big data era by combining the familiarity of relational databases with the scale and agility of Hadoop/NoSQL systems. With nearly two and half years of solid engineering effort building this next generation SQL technology, and backed by a strong community of ~50 contributors and thousands of users and customers across various industries, Apache Drill has quickly evolved to become the most flexible SQL query engine in the big data ecosystem since the Beta release in September 2014. Built from the ground up to support interactive queries on a variety of complex/multi-structured datasets at TB/PB scale, Drill opens up new frontiers for the innovation required to make Hadoop and big data accessible for a broader set of users in a self-service fashion, leveraging the ANSI SQL skill sets and tools already abundant as part of an organization’s BI/analytics infrastructure.

A look back at the journey

Here is a quick snapshot of the momentum of the Apache Drill project along with some notable milestones along the way. The project has been on the fast track in the last nine months since the developer preview in August 2014, delivering seven significant iterative releases, each adding exciting new features and most importantly, improving on the stability, scale, and performance required for broader enterprise deployments. Overall, 2200+ JIRAs have been resolved in this effort. Thanks to the excellent progress, numerous customers have used and experienced the value of Drill and have rolled it into production. Drill also graduated as an Apache Top-Level Project during the journey, and is recognized as the top-rated SQL-on-Hadoop technology by industry analysts. Read more

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