Introducing Revolution R Open and Revolution R Plus

October 15, 2014
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

For the past 7 years, Revolution Analytics has been the leading provider of R-based software and services to companies around the globe. Today, we're excited to announce a new, enhanced R distribution for everyone: Revolution R Open.

Revolution R Open is a downstream distribution of R from the R Foundation for Statistical Computing. It's built on the R 3.1.1 language engine, so it's 100% compatible with any scripts, packages or applications that work with R 3.1.1. It also comes with enhancements to improve your R experience, focused on performance and reproducibility: 

  • Revolution R Open is linked with the Intel Math Kernel Libraries (MKL). These replace the standard R BLAS/LAPACK libraries to improve the performance of R, especially on multi-core hardware. You don't need to modify your R code to take advantage of the performance improvements.
  • Revolution R Open comes with the Reproducible R Toolkit. The default CRAN repository is a static snapshot of CRAN (taken on October 1). You can always access newer R packages with the checkpoint package, which comes pre-installed. These changes make it easier to share R code with other R users, confident that they will get the same results as you did when you wrote the code.

Today we are also introducing MRAN, a new website where you can find information about R, Revolution R Open, and R Packages. MRAN includes tools to explore R Packages and R Task Views, making it easy to find packages to extend R's capabilities. MRAN is updated daily.

Revolution R Open is available for download now. Visit mran.revolutionanalytics.com/download for binaries for Windows, Mac, Ubuntu, CentOS/Red Hat Linux and (of course) the GPLv2 source distribution.

With the new Revolution R Plus program, Revolution Analytics is offering technical support and open-source assurance for Revolution R Open and several other open source projects from Revolution Analytics (including DeployR Open, ParallelR and RHadoop). If you are interested in subscribing, you can find more information at www.revolutionanalytics.com/plus . And don't forget that big-data R capabilities are still available in Revolution R Enterprise.

We hope you enjoy using Revolution R Open, and that your workplace will be confident adopting R with the backing of technical support and open source assurance of Revolution R Plus. Let us know what you think in the comments! 

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

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