Benchmarking results compare speed of Revolution R Enterprise and legacy SAS

May 28, 2014
By

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

Many companies are considering switching from SAS to R for statistical data analysis, and may be wondering how R compares in performance and data size scalability to the legacy SAS systems (base SAS and SAS/Stat) they are currently using. Performance and scalability for R is exactly what Revolution R Enterprise (RRE) was designed for. In a recent webinar, Thomas Dinsmore described a benchmarking process to compare performance of legacy SAS and RRE. (The benchmarking process is described in the white paper Revolution R Enterprise: Faster Than SAS, and you can see the code behind the benchmarking process here.) In the webinar, Thomas revealed the following results:

  • RRE ran the tasks forty-two times faster than legacy SAS on the larger data set
  • RRE outperformed legacy SAS on every task
  • The RRE performance advantage ranged from 10X to 300X
  • The RRE advantage increased when we tested on larger data sets
  • SAS’ new HP PROC, where available, only marginally improved SAS performance

Also in the webinar, John Wallace, founder and CEO of DataSong, described how performance and scalability requirements led to the selection in 2011 of Revolution R Enterprise as the analytics engine in their software-as-a-service platform. DataSong's industry-leading marketing analytics system currently analyzes more than $3billion in marketing spend by major retailers.

The slides from the webinar are embedded above, and you can watch and download the full webinar at the link below.

Revolution Analytics webinars: Is Revolution R Enterprise Faster than SAS? Benchmarking Results Revealed

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

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)