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October 15, 2014
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Bringing 100% open source Hadoop to Azure Infrastructure as a Service (IaaS)

More and more enterprises are looking to the cloud as a place to handle a variety of their data processing and backup needs. Apache Hadoop lends itself to running in cloud environments because of the alignment around scalability and flexibility for compute and storage offered with today’s cloud infrastructures. Today, we are excited to announce that the Hortonworks Data Platform (HDP) is the first platform to be certified to run on Azure Infrastructure as a Service. This gives customers new deployment choices for small and large deployments in the cloud. With this new certification, Hortonworks and Microsoft are making Apache Hadoop more widely available and easy to deploy for data processing and analytic workloads enabling the enterprise to expand their Modern Data Architecture (MDA).

This certification expands the deployment options for Microsoft customers by providing them with complete interoperability between workloads on-premises and in the cloud. This means that applications built on-premises can be moved to the cloud seamlessly. It also means that data analytics first created and validated in the cloud can be moved on-premises. There is complete compatibility between these infrastructures giving customers the freedom to use the infrastructure that best meets their needs. You can backup data where the data resides (geographically) and provide the flexibility and opportunity for others to do Hadoop analytics in the cloud (globally).

A History of Delivering Hadoop to Microsoft Customers

Hortonworks and Microsoft have been partnering to deliver solutions for big data on Windows since 2011. Hortonworks is the company that Microsoft relies on for Hadoop on Windows providing the only 100% native windows distribution as well as the core platform for HDInsight and the Hadoop region of the Analytics Platform System.

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We are excited to be the first Hadoop vendor to offer Hadoop on Azure IaaS and we will continue our long history of working with Microsoft to engineer and offer solutions that meet the most flexible and easy to use deployment options for big data available, further increasing the power of the modern data architecture.

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