With an enthusiastic world-wide user base estimated at 2M and a stranglehold on academia, there's no doubt that the future for open source R Project for Statistical Computing is bright. Yet even with this largesse the challenges for commercial R purveyor Revolution Analytics (formerly REvolution Computing) are significant.

In the current data deluge era, the R limitation that a data set being analyzed must reside entirely in computer memory is seen as draconian. And R's interpretive language can be quite inefficient for “big” algorithms and computations. Indeed, the knock on R is that it's good for prototyping but doesn't scale. Competitors like SAS have a head start in scaling analytics, collaborating with hardware and database vendors to optimize for “big data” processing.

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