In what he terms “yet another example of the remarkable innovation occurring in the open source Big Data Community,” Wikibon Big Data Analyst Jeff Kelly writes that a small group of committers is developing an open source SQL-like query tool for Hadoop databases called “Apache Drill”.

Designed after BigQuery, Google’s Big-Data-Analytics-as-a-Service technology that it made publicly available in May, Apache Drill is meant to compliment MapReduce, allowing business people to get answers to specific questions such as “what time of day is most popular for app downloads” from Apache Hadoop Big Data databases directly in seconds. MapReduce, by contrast, is a much more technically complex query languages for use by professional Data Scientists to answer much larger questions such as identifying hidden customer behavior patterns from years of unstructured data.

Apache Drill is far from ready for general use, however. It is presently in incubator status with eight committers, including two from MapR, actively developing it. Kelly notes that some MapR projects have remained closed source. However, MapR executives say they are committed to keeping Drill open source because they believe that the open source community can help drive development faster than an internal team.

Given the project’s immaturity, Kelly recommends that organizations with immediate needs for real-time Big Data query support consider alternative approaches including the Google BigQuery service while keeping an eye on Drill’s progress.

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