Microsoft Azure Data Updates Continue Open Source Trend
One day after Big Data player Pivotal Software Inc. changed its business model by open sourcing core technologies, Microsoft today announced related product updates with a definite open source slant.
The "new and enhanced" data services include an Azure HDInsight preview that runs on Linux, and the general availability of Storm on HDInsight, Azure Machine Learning, and Informatica technology on the Microsoft Azure cloud.
"Just about every interesting innovation that's going on -- in data today, in machine learning and other areas -- has its roots in an open source ecosystem," Pivotal CEO Paul Maritz said yesterday at a live streaming event.
Perhaps an exaggeration, but the underlying meaning was grokked by Microsoft years ago, and the company is in the middle of a swing to openness and interoperability, led by new CEO Satya Nadella and top lieutenants such as T. K. "Ranga" Rengarajan, head of the data platform.
"Azure Machine Learning reflects our support for open source," stated a blog post today authored by Rengarajan and machine learning exec Joseph Sirosh. "The Python programming language is a first-class citizen in Azure Machine Learning Studio, along with R, the popular language of statisticians." Microsoft acquired stewardship of the R language earlier this year.
Data developers can now use the Machine Learning Marketplace to discover appropriate APIs and prebuilt services for common concerns such as recommendation engines, detecting anomalies and forecasting.
The open source story continues with Storm for Azure HDInsight. Azure HDInsight is Microsoft's cloud service based on 100 percent Apache Hadoop technology, open sourced by the Apache Software Foundation.
"Storm is an open source stream analytics platform that can process millions of data 'events' in real time as they are generated by sensors and devices," Microsoft said. "Using Storm with HDInsight, customers can deploy and manage applications for real-time analytics and Internet-of-Things (IoT) scenarios in a few minutes with just a few clicks. We are also making Storm available for both .NET and Java and the ability to develop, deploy and debug real-time Storm applications directly in Visual Studio. That helps developers to be productive in the environments they know best." Microsoft added Storm integration last fall.
Of course, there's nothing more open source than the Linux OS, and Azure HDInsight is now available as a preview project running on Ubuntu clusters. Ubuntu is a popular Linux distribution, described by Microsoft as "the leading scale-out Linux."
Adding Linux support in addition to Windows "is particularly compelling for people that already use Hadoop on Linux on-premises like on Hortonworks Data Platform, because they can use common Linux tools, documentation, and templates and extend their deployment to Azure with hybrid cloud connections," Microsoft said.
Also, to increase customer options for leveraging technology from Microsoft partners, the Redmond software giant announced that Informatica data integration technology will be available in the Azure Marketplace.
"Today, Informatica is announcing the availability of its Cloud Integration Secure Agent on Microsoft Azure and Linux Virtual Machines as well as an Informatica Cloud Connector for Microsoft Azure Storage," Informatica exec Ronen Schwartz said in a blog post today. "Users of Azure data services such as Azure HDInsight, Azure Machine Learning and Azure Data Factory can make their data work with access to the broadest set of data sources including on-premises applications, databases, cloud applications and social data."
All the Microsoft news comes during the Strata + Hadoop World conference underway in San Jose, Calif.
"These new services are part of our continued investment in a broad portfolio of solutions to unlock insights from data," Microsoft said. "They can help businesses dramatically improve their performance, enable governments to better serve their citizenry, or accelerate new advancements in science. Our goal is to make Big Data technology simpler and more accessible to the greatest number of people possible: Big Data pros, data scientists and app developers, but also everyday businesspeople and IT managers."
Posted by David Ramel on 02/18/2015 at 10:27 AM