Microsoft adds Apache Storm analytics-processing support to Hadoop on Azure

Microsoft's HDInsight Hadoop-on-Azure service is getting Apache Storm real-time analytics support in preview form.
Written by Mary Jo Foley, Senior Contributing Editor

Microsoft is making available as of October 15 a preview of Apache Storm for its HDInsight Hadoop-on-Azure service.


Microsoft officials are touting the addition of Storm support as key to allowing customers to "process millions of items of Hadoop data from their Internet of Things devices in near real time using a fully managed Hadoop service."

Apache Storm is a free, open-source system for processing streaming data in real time in Hadoop 2.x. Storm can be used with a variety of programming language and provides processing support for realtime analytics, machine learning, and other tasks. Amazon's AWS already supports Storm.

HDInsight is Microsoft's cloud-based distribution of Hadoop which it developed in conjunction with Hortonworks.

Microsoft officials announced the Apache Storm news in conjunction with the Strata + Hadoop World show in New York.

Microsoft also is introducing new machine-learning capabilities into the Azure Marketplace to allow customers and partners to take advantage of new functionality in the form of Web services.

One of the new services is a recommendation engine for adding product recommendations to a Web site. (I wouldn't be surprised if this recommendation engine has ties to Microsoft's "Project Sage" recommendation-as-a-service work.) Other new machine-learning services available in the Marketplace include an anomaly-detection service for predictive maintenance or fraud detection, as well as a set of R programming-language packages.

Microsoft made available a preview of its own machine-learning service on Azure, Azure ML, in June 2014.

In related news, Hortonworks announced today that the next version of the Hortonworks Data Platform (HDP) will include hybrid data connectors that will enable customers to extend their on-premise Hadoop deployments to Azure and leverage the cloud for backup, scale and testing.

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