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DataTorrent Makes Big Data Analytics More Accessible

Four Steps to Ensure Your Big Data Investment Pays Off In addition to announcing that it is making its core engine available as an open source Project Apex technology, DataTorrent has released an update to its Big Data analytics software for Hadoop that eliminates the dependencies organizations now have on developers to create these applications. […]

Written By
MV
Mike Vizard
Jun 8, 2015
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Four Steps to Ensure Your Big Data Investment Pays Off

In addition to announcing that it is making its core engine available as an open source Project Apex technology, DataTorrent has released an update to its Big Data analytics software for Hadoop that eliminates the dependencies organizations now have on developers to create these applications.

John Fanelli, vice president of marketing for DataTorrent, says the latest version of DataTorrent enables individuals to assemble Big Data analytics applications without having to write code. In addition, end users can make use of a library of visualizations to create dashboards in a matter of minutes.

Finally, DataTorrent 3.0 comes with pre-built connectors for integrating with both enterprise applications and custom Java applications in addition to graphical tools that make it simpler to ingest data into a Big Data application.

Fanelli contends that the thing that differentiates DataTorrent most is that in addition to being simpler to deploy and use, it can support both streaming and batch applications. In contrast, Fanelli says open source technologies such as Apache Storm or Apache Spark Streaming are less mature technologies that require a lot more engineering expertise to set up and deploy.

DataTorrent

By launching its own open source project, DataTorrent is clearly trying to build a large community around its core technology that will result in more demand for the suite of application development tools that the company sells on top of its core engine.

The degree to which that strategy succeeds remains to be seen. But there’s no doubt that the demand for Big Data analytics applications is far outstripping the current ability of the developer community to service. As such, it’s only a matter of time before organizations start looking for other ways to gain access to those applications.

MV

Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

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