Last week, Joseph Sirosh, Corporate Vice President of the Microsoft Data Group, announced the general availabilty of Microsoft R Server, laying the foundation for making R the enterprise standard for cross-platform analytics, both on-premises and in the cloud.
Microsoft R Server is built on the highly popular open source R language, and adds enterprise scale & performance, operationalization and multi-platform support. R scripts built for the Microsoft R Server can work on data much larger than physical memory, support multi-threaded and distributed execution of scripts thus delivering superior performance, enable quick deployment by providing web services end-points for R script integration into LOB applications, and runs on a wide variety of platforms.
Here is an example illustrating the performance and scale of Microsoft R Server’s Scale-R technology compared with equivalent open source R functions. The Open Source R glm() function is able to process less than 500K observations and it took about 78 seconds; the equivalent rxGlm() function in scale-R is able to process over 5MM observations in under 10 seconds and has a very gradual linear increase in time. Basically, the rxGlm() function is limited only by the size of the physical disk on the machine and not by the main memory.
One important highlight in this launch announcement is the availability of free developer versions of all of our commercial servers for R for development purposes. This greatly reduces the friction for adoption and driving usage of R Servers and Services. Mary Jo Foley called this out in her blog.
How to Get Started?
- Download Microsoft R Server Developer Edition for free
- Get started with development using the Microsoft Data Science Virtual Machine on Azure now. For production purposes use these Azure Marketplace VMs
- Check out R Tools for Visual Studio product video and sign up for early access by emailing RTVS-Invite@microsoft.com
- Sign-up for our upcoming webinar series on R and Microsoft R Server.
- High level overview of Data Science with R
- The Fundamentals of the R Language
- Introduction to Revolution R Enterprise
- Performance and Scale Options for R with Hadoop: A comparison of potential architectures
- Microsoft R Forum