Hadoop Apps Without MapReduce Mindsets

Big data application platform company Concurrent has announced Lingual, an open source project for application development on Apache Hadoop. The Lingual offering centers around the chance for SQL users to create and run big data applications on Hadoop without any new training or having to think in MapReduce.

Analysts and developers, familiar with SQL, JDBC, or traditional BI tools, can use this new tool to create and run big data apps. Lingual presents a true ANSI-standard SQL interface and is compatible with all major Hadoop distributions, whether on-premise or in the cloud.

Lingual use-case examples include those utilized by developers who want to "cut and paste" existing ANSI SQL code from traditional data warehouses and instantly access data locked on a Hadoop cluster.

NOTE: Developers can use a standard Java JDBC interface to create new Hadoop applications, or use any of the Cascading APIs and languages, such as Scalding and Cascalog. Being ANSI-standard compliant, companies can now query and export data from Hadoop directly into traditional BI tools.

Chris Wensel, CEO and founder of Concurrent, explains that Cascading is also at the core of language extensions including PyCascading (Python + Cascading), Scalding (Scala + Cascading), and Cascalog (Clojure + Cascading) — open source projects sponsored by Twitter.