MapR-based Hadoop Clusters Coming to the Azure Marketplace 

1 min read

Microsoft is committed to continuous innovation to make Azure the best cloud platform for running hyper-scale big data projects. This includes an existing Hadoop-as-a-service solution, Azure HDInsight, a hyper-scale repository for big data, Azure Data Lake, and Hadoop infrastructure-as-a-service offerings from Hortonworks and Cloudera. This week, Hortonworks also announced their most recent milestone with Hortonworks Read more

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The Best of Both Worlds: Top Benefits and Scenarios for Hybrid Hadoop, from On-Premises to the Cloud 

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Historically, Hadoop has been a platform for big data that you either deploy on-premises with your own hardware or in the cloud and managed by a hosting vendor. Deploying on-premises affords you specific benefits, like control and flexibility over your deployment.  But the cloud provides other benefits like elastic scale, fast time to value, and Read more

Cloudera Selects Azure as a Preferred Cloud Platform 

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We are working to make Azure the best cloud platform for big data, including Apache Hadoop. To accomplish this, we deliver a comprehensive set of solutions such as our Hadoop-based solution Azure HDInsight and managed data services from partners, including Hortonworks. Last week Hortonworks  announced the most recent milestone in our partnership and yesterday we Read more

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Microsoft announces real-time analytics in Hadoop and new ML capabilities in Marketplace 

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This morning at Strata + Hadoop World, Microsoft announced the preview of Apache Storm clusters inside HDInsight as well as new machine learning capabilities in the Azure Marketplace. Apache Storm is an open source project in the Hadoop ecosystem which gives users access to an event-processing analytics platform that can reliably process millions of events. Read more

Microsoft releases HDInsight for Hadoop 2.4 And Gains 100x Performance Increase 

2 min read

Yesterday at the Hadoop Summit, Microsoft announced that Azure HDInsight now supports Hadoop 2.4.  This is the next release of our 100 percent Apache Hadoop-based distribution for Microsoft Azure. In conjunction with Hortonworks recent release of HDP 2.1 as a Hadoop on Windows offering and Analytics Platform System as a Hadoop and data warehousing appliance, this Read more

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Microsoft updates its Hadoop cloud solution 

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Hadoop Summit kicked of today in San Jose, and T. K. Rengarajan, Microsoft Corporate Vice President of Data Platform, delivered a keynote presentation where he shared Microsoft’s approach to big data and the work we are doing to make Hadoop accessible in the cloud. At the event, we also announced that Azure HDInsight, our Hadoop-based service Read more

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Hortonworks Makes HDP 2.0 for Windows Server Generally Available 

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Today, Hortonworks announced the general availability of the Hortonworks Data Platform (HDP) 2.0 for Windows.  This is the next release of the industry’s only 100% Apache Hadoop-based distribution for Windows. With Windows Server leading all operating system  in usage share (two out of every three servers run Windows Server), HDP 2.0 for Windows dramatically broadens the Read more

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Gartner BI Summit 2013: Bringing Hadoop to the Enterprise 

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Gartner’s annual Business Intelligence & Analytics Summit kicked off earlier today where we are focused on sharing our perspective and solutions with customers, partners and industry leaders interested in big data and business intelligence. Later this week, we’ll also be at the GigaOM Structure event. While we’re out attending all these industry events, our engineering Read more

Hortonworks and Microsoft Bring the Hortonworks Data Platform to Windows 

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Today, Hortonworks released the beta for the Hortonworks Data Platform (HDP) for Windows, the industry’s first 100% Open Source Apache Hadoop-based distribution for Windows. With Windows Server holding 73% marketshare in 2012*, HDP for Windows dramatically broadens the accessible market for Hadoop. This release is the result of a deep engineering partnership between Hortonworks and Read more

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