Revolution Pumps up Performance in Big Data Analytics App
Revolution Analytics, a commercial provider of software and services based on the open source R project for statistical computing, introduced its Revolution R Enterprise 6.0 analytics software, which is designed to enable statistical analysis of Big Data.
According to the company, the software’s built-in RevoScaleR package allows R users to process, visualize and model terabyte-class data sets in a fraction of the time of legacy products – without using specialized hardware. Among the new features of Revolution R Enterprise 6.0:
- Platform LSF Cluster Support, which supports distributed computing on multi-node Platform LSF grids. Support on Windows-based grids is provided via Microsoft HPC Server.
- Cloud-based Analytics with Azure Burst, which allows users to switch computations from a local Microsoft Windows HPC Server cluster to the Azure Cloud with a single command.
- Big-Data Generalized Linear Models, which supports predictive models used in insurance, finance and biotech industries.
- Direct Analysis of SAS, SPSS, ASCII and ODBC Data, which allows users to analyze proprietary data formats without the need for SAS/SPSS licenses.
- Updated R 2.14.2 Engine, which the company says improves performance and parallel programming capabilities. Revolution Analytics’ open-source RHadoop project (for Hadoop integration) has been updated to work with this new engine.
A company announcement includes a statement from John Wallace, CEO of UpStream Software, a Revolution Analytics customer. “We’ve combined Revolution R Enterprise and Hadoop to build and deploy customized exploratory data analysis and GAM survival models for our marketing performance management and attribution platform,” Wallace said. “Given that our data sets are already in the terabytes and are growing rapidly, we depend on Revolution R Enterprise’s scalability and fast performance. We saw about a 4x performance improvement on 50 million records.”
Revolution Analytics is one of the leading proponents for R, having provided the first commercial distribution of R in 2007. As David Smith, Revolution’s vice president of marketing and community, told Enterprise Apps Today earlier this year, a combination of Hadoop and open source R offers a clear path for enterprises to move from processing and storing Big Data to analyzing it. Revolution sponsored a contest to illustrate the Big Data analysis potential of R, awarding cash prizes and licenses to its analytics software to several winning entries.
The company says R is used by more than two million analysts in academia and at companies such as Google and Bank of America. Revolution Analytics is committed to fostering R adoption by sponsoring the Inside-R.org community site, funding worldwide R user groups and offering free licenses of Revolution R Enterprise to members of academia.
