This week, Concurrent Inc. announced details of Lingual, a project designed to facilitate adoption of Apache Hadoop by empowering SQL users to leverage their SQL skills to create applications applications that run on Hadoop without training in MapReduce. Lingual presents developers with an ANSI-standard SQL interface that is compatible with all major Hadoop distributions. Using Lingual, developers can utilize SQL code to run against data stored within Hadoop clusters. Moreover, developers and data scientists can use Lingual to export data directly into BI tools. Developers can also use Lingual to create new Hadoop-based applications using the platform’s JDBC interface or Cascading APIs and languages, such as Scalding and Cascalog. Lingual runs on Concurrent’s Cascading platform for simplifying Hadoop development for Java developers. Cascading allows developers to use Java languages to create processes and applications within a Hadoop cluster without learning the intricacies of MapReduce. Lingual represents a fitting extension of Cascading’s mission to facilitate the development of applications that run against Hadoop clusters by expanding the required developer skill-set from Java to include SQL.