Microsoft Closes Acquisition of Revolution Analytics

This blog post is authored by Joseph Sirosh, Corporate Vice President of Information Management & Machine Learning at Microsoft.

Earlier this year we announced our intent to acquire Revolution Analytics and today I’m happy to say we have closed the acquisition agreement.

It is my pleasure to welcome the Revolution team to Microsoft. Together we will help unlock the power of the R language for advanced analytics on big data.

R is the world’s most popular programming language for statistical computing and predictive analytics, used by more than 2 million people worldwide. Revolution has made R enterprise-ready with speed and scalability for the largest data warehouses and Hadoop systems. For example, by leveraging Intel’s Math Kernel Library (MKL), the freely available Revolution R Open executes a typical R benchmark 2.5 times faster than the standard R distribution and some functions, such as linear regression, run up to 20 times faster. With its unique parallel external memory algorithms, Revolution R Enterprise is able to deliver speeds 42 times faster than competing technology from SAS.

Moving forward, we will build R and Revolution’s technology into our data platform products so companies, developers and data scientists can use it across on-premises, hybrid cloud and Azure public cloud environments. For example, we will build R into SQL Server to provide enormously fast and scalable in-database analytics that can be deployed in an enterprise customer’s datacenter, on Azure, or in a hybrid combination. In addition, we will integrate Revolution’s scalable R distribution into Azure HDInsight and Azure Machine Learning, making it much easier and faster to analyze big data, and to operationalize R code for production applications. We will also continue to support running Revolution R Enterprise across heterogeneous platforms including Linux, Teradata and Hadoop deployments. No matter where their data lives, customers and partners will be able to take advantage of R more quickly, simply and cost effectively than ever before.

As I said in January, we are excited to foster the open source evolution of R fueled by its active, passionate community. We are excited to support and amplify Revolution’s open source projects such as the fast Revolution R Open distribution, the ParallelR collection of packages for distributed programming, Rhadoop for running R on Hadoop nodes, DeployR for deploying R analytics in web and dashboard applications, the Reproducible R Toolkit and RevoPemaR for writing parallel external memory algorithms. We will continue to support and evolve these and the commercial distributions of Revolution R across multiple operating systems.

As part of our commitment to help close the data scientist and analytics skills gap, we will also carry forward Revolution’s efforts to educate and train aspiring developers and data scientists who want to learn R, leveraging the breadth and depth of our global programs and partner ecosystem.

I am excited about the road ahead as we bring enterprise grade R implementations to the most widely used database in the world and to the reach and scale of Azure. For those of you who plan to attend Build 2015 or Ignite, I will share more information about Revolution’s products at my keynotes sessions there, including demos and our roadmap – so please do tune in. We’ll also share more information on this blog as we progress forward. For now, if you have suggestions or feedback, please share them with us here.

You can also read a blog post by David Smith, chief community officer at Revolution Analytics, here.

Joseph