Attunity Brings Scientists Closer to the Data with Fresh Hadoop App

Attunity, a Boston-based enterprise software developer, unveiled a new version of its data replication solution for Hadoop. The update allows for more efficient transfer of information to, and from the analytics engine.

Attunity RepliWeb for Enterprise File Replication (EFR) 6.0 features dashboards and notifications that make it possible to monitor large-scale movements from within the application interface. In addition, new data management capabilities are available on Windows, Unix and Linux, and the underlying technology has been improved to deliver better performance.

ERP 5.0 also features support for several new platforms and services, including  AWS S3 (via Attunity CloudBeam), and Hadoop distributions  from Greenplum and Hortonworks.

“Increasingly, organizations are using Apache Hadoop because of its ability to store and process hundreds of terabytes to petabytes of data across thousands of servers, while providing a means to run jobs across those machines efficiently,” explained Mitch Ferguson, vice president of business development at Hortonworks. “Hadoop is unique because of its ability to process massive amounts of data. Hortonworks shares Attunity’s vision to help organizations bridge the gap between Hadoop and Big Data sources more quickly, easily and affordably.”

Indeed, Apache Hadoop has spurred initiative across the board.  About two weeks ago Hortonworks unveiled a desktop edition of Hadoop that is completely free, and relatively easy to deploy.  This scaled-down version is based on the latest release of Hortonworks’ flagship distribution, which also puts a big emphasis on usability.

HDP 1.2 comes pre-integrated with Ambari, a configuration tool for Hadoop available under the Apache license. V1.2 features several other enhancements as well, including a reworked architecture that delivers better performance and support for multi-thread queries to Hive.  Hortonworks also touts a connector that offers improved integration with traditional database systems.