A company focused on R, the open-source language for statistical analysis, relaunched under a new name Tuesday and gave a preview of its technology roadmap for 2010.
Revolution Analytics, formerly known as Revolution Computing, is headed by CEO Norman Nie, co-founder of predictive analytics vendor SPSS, and R co-creator Robert Gentleman sits on its board.
To date, the startup has offered an R development environment called Revolution R Enterprise, as well as commercial training and support.
R was initially created by Ross Ihaka and Gentleman at the University of Auckland in New Zealand. It now boasts a thriving community, and a large body of add-on packages have been created for the core toolset.
Hoping to gain a stronger foothold at the grassroots level, the company is now offering a single workstation license of Revolution R Enterprise at no cost to academic users, although costs would kick in if they desire support. It is also launching a portal, inside-R.org, for R advocates and users.
Its product releases for the remainder of 2010 will include technology for processing very large data sets; an easier-to-use, Web-based user interface aimed at business analysts, not programmers; and new services and products for helping customers migrate over to R.
The company is also planning to form many partnerships with BI (business intelligence) and database vendors, according to chief operating officer Jeff Erhardt. Also, "everything we're building is in a cloud-ready form," he added. "As we move forward, [customers] will be able to do cloud implementations."
This represents a validation of R more than a threat, according to Revolution Analytics.
The company's software is priced "aggressively" versus IBM and SAS. A single supported workstation costs $2,000 for an annual subscription. Pricing for server-based licenses varies depending on the implementation.
But Revolution Analytics faces a tough challenge from those larger vendors, as well as the likes of XLSolutions, which offers R training and a competing software package, R-Plus.
The integration of SAS Institute's technology with various MPP (massively parallel processing) databases, for example, "promises to be very powerful, scalable, and functional, once it is fully available," said analyst Curt Monash of Monash Research. "It's hard to see how a startup -- even an R-based one -- could offer better technology."
That's not to say it has no chance.
"It's easy to see how an alternative could be much less expensive, yet still get the work done," Monash added.