On Tuesday, Hortonworks announced the general availability of version 2.0 of the Hortonworks Data Platform for Windows. Hortonworks Data Platform 2.0 for Windows is the first distribution of Apache Hadoop 2.0 certified for Windows Server 2008 R2 and Windows Server 2012. Today’s announcement means that YARN (Yet Another Resource Negotiator), a key feature of Hadoop 2.0, is now available to Windows-based development environments. With HDP 2.0, developers in Windows shops can take advantage of YARN’s transformation of Hadoop from an infrastructure for batch processing to batch and real-time data processing. Moreover, HDP 2.0 features the NameNode High Availability functionality automates failovers and ensures the availability of the full HDP stack. Hortonworks collaborated closely with Microsoft in order to ensure the HDP 2.0 release achieved production-grade status within Windows environments. The release of HDP 2.0 marks yet another milestone in the story of the democratization of Apache Hadoop, the Big Data platform that is being rendered increasingly available to wider circles of users by means of initiatives such as Stinger (Hortonworks), Lingual (Concurrent) and Impala (Cloudera) that allow users to access and manipulate data stored in a Hadoop cluster using SQL.
Tag: Lingual
Concurrent Announces Lingual To Facilitate Hadoop Adoption For SQL Users
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.
Cloud Computing Today 