Since we've had quite a few announcements over the last month or so, I thought I'd take a moment to catch up on some of the media reports mentioning Revolution Analytics.
Last week, Gartner revealed Revolution Analytics as a Visionary in the new Magic Quadrant for Advanced Analytics Platforms. Inside BigData noted that "Alteryx, Revolution Analytics, RapidMiner and Knime are the ones to watch in 2014", while SearchBusinessAnalytics also noted that "Revolution Analytics also received high marks". Enterprise Apps Today notes the prominence of open-source vendors in the Quadrant, and quotes me saying "traditional enterprise tools struggle to match the open-source community's ability to innovate, iterate and evolve rapidly". Meanwhile, Datanami noted that while SAS and IBM are "King of [the] Analytics Hill" for now, the question is, "But for how long"? and summarized Revolution Analytics' position in the Magic Quadrant:
Revolution Analytics also fared quite well in Gartner's Magic Quadrant. The Mountain View, California-based company is credited with realizing the power of open source R, and has therefore become "the default choice for organizations without an existing provider seeking an R-based solution." High customer satisfaction and a strong sales pipeline are strengths.
Last month we also announced that Revolution R Enterprise is now available in the Amazon Cloud, with instances on Windows and Linux — including RStudio Server Pro — available on a pay-as-you go model for just $0.70 per core per hour (even less than the prices listed in Network World's New Product of the Week slideshow). ComputerWorld says this cloud-based service provides "an easy way for individuals and organizations to start and test their big-data-styled analysis projects". IT BusinessEdge notes that "users of the AWS service can run computations on data sets up to 1TB on Windows and Linux servers".
Finally, our director of product management Thomas Dinsmore was honored with an article for Wired Innovation Insights, on building smarter organizations that include data scientists, power analysts, business analysts and analytic consumers.