Data Driver

Blog archive

Cloudera Big Data Partnership Adds Azure Options

In Microsoft's new era of openness, interoperability and increased customer options, the company continues to hedge its Big Data bets with a stream of new partnerships, services and initiatives.

The company's continued expansion of data developer services in Microsoft Azure cloud was highlighted this week by a partnership with Cloudera Inc., one of the "big three" Big Data players with enterprise offerings based on Apache Hadoop.

Cloudera Enterprise this week achieved Azure Certification to offer more Big Data options for Microsoft cloud customers, and further integration of Cloudera technology with other Microsoft data services is on tap.

"As a result of this certification, organizations will be able to launch a Cloudera Enterprise cluster from the Azure Marketplace starting Oct. 28," Microsoft said in a blog post. "Initially, this will be an evaluation cluster with access to MapReduce, HDFS and Hive. At the end of this year when Cloudera 5.3 releases, customers will be able to leverage the power of the full Cloudera Enterprise distribution including HBase, Impala, Search and Spark."

Just last week, Hortonworks Inc. -- another of the top three Hadoop vendors and a principal competitor to Cloudera -- announced Azure certification for its Hortonworks Data Platform (HDP). This expands on the partnership of Microsoft and Hortonworks, which last year teamed up for the Microsoft cloud-based Hadoop service, HDInsight, and earlier developed HDP for Windows.

Also last week, Microsoft announced HDInsight integration with Apache Storm for real-time Big Data analytics.

In the latest move with Cloudera, Azure customers will have more Big Data options, especially after Cloudera 5.3 is released in December. Then, Cloudera said, customers will be able to:
  • Deploy Cloudera directly from the Microsoft Azure Marketplace.
  • Import data into Cloudera from SQL Server.
  • Use Microsoft Power BI for Office 365 for self-service business intelligence.
  • Use Azure Machine Learning for cloud-based predictive analytics.

The SQL Server functionality is a further sign of Microsoft's tremendous effort to keep its traditional flagship relational database management system (RDBMS) relevant in the new world of Big Data analytics powered by non-relational NoSQL databases. Partnerships with Big Data vendors are key to that strategy, and Microsoft has now teamed up with two of the leading enterprise offerings in major initiatives.

"Microsoft and Cloudera are collaborating to help customers realize Big Data insights with the cloud," said Microsoft exec Scott Guthrie in a statement. "Now Azure customers can deploy Cloudera Enterprise with a few clicks, visualize their data with Microsoft Power BI and gain insights to transform their business -- all within minutes."

Stay tuned for further partnership news, possibly even with the third leading Hadoop vendor, MapR Technologies Inc.

Posted by David Ramel on 10/23/2014


comments powered by Disqus

Featured

  • Cloud-Focused .NET Aspire 9.1 Released

    Along with .NET 10 Preview 1, Microsoft released.NET Aspire 9.1, the latest update to its opinionated, cloud-ready stack for building resilient, observable, and configurable cloud-native applications with .NET.

  • Microsoft Ships First .NET 10 Preview

    Microsoft shipped .NET 10 Preview 1, introducing a raft of improvements and fixes across performance, libraries, and the developer experience.

  • C# Dev Kit Previews .NET Aspire Orchestration

    Microsoft's dev team has been busy updating the C# Dev Kit, a Visual Studio Code extension that enhances the C# development experience by providing tools for managing, debugging, and editing C# projects.

  • Hands On: New VS Code Insiders Build Creates Web Page from Image in Seconds

    New Vision support with GitHub Copilot in the latest Visual Studio Code Insiders build takes a user-supplied mockup image and creates a web page from it in seconds, handling all the HTML and CSS.

  • Naive Bayes Regression Using C#

    Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the naive Bayes regression technique, where the goal is to predict a single numeric value. Compared to other machine learning regression techniques, naive Bayes regression is usually less accurate, but is simple, easy to implement and customize, works on both large and small datasets, is highly interpretable, and doesn't require tuning any hyperparameters.

Subscribe on YouTube

Upcoming Training Events