As a proud member of the Apache Software Foundation, it’s always great to see the growth and adoption of Apache community projects. The Apache Hadoop project is a prime example. Last year I blogged about how Microsoft was engaging with this vibrant community, Microsoft, Hadoop and Big Data. Today, I’m pleased to relay the news about increased interoperability capabilities for Apache Hadoop on the Windows Server and Windows Azure platforms and an expanded Microsoft partnership with Hortonworks.
Microsoft Technical Fellow David Campbell announced today new previews of Windows Azure HDInsight Service and Microsoft HDInsight Server, the company’s Hadoop-based solutions for Windows Azure and Windows Server.
Here’s what Dave had to say in the official news about how this partnership is simplifying big data in the enterprise.
“Big Data should provide answers for business, not complexity for IT. Providing Hadoop compatibility on Windows Server and Azure dramatically lowers the barriers to setup and deployment and enables customers to pull insights from any data, any size, on-premises or in the cloud.”
Dave also outlined how the Hortonworks partnership will give customers access to an enterprise-ready distribution of Hadoop with the newly released solutions.
And here’s what Hortonworks CEO Rob Bearden said about this expanded Microsoft collaboration.
“Hortonworks is the only provider of Apache Hadoop that ensures a 100% open source platform. Our expanded partnership with Microsoft empowers customers to build and deploy on platforms that are fully compatible with Apache Hadoop.”
An interesting part of my open source community role at MS Open Tech is meeting with customers and trying to better understand their needs for interoperable solutions. Enhancing our products with new Interop capabilities helps reduce the cost and complexity of running mixed IT environments. Today’s news helps simplify deployment of Hadoop-based solutions and allows customers to use Microsoft business intelligence tools to extract insights from big data.