Vendor news: TIBCO’s proprietary R runtime; Teradata’s appliance integrates R

In a webinar today previewing Spotfire 5 (scheduled for release this November), TIBCO announced that it will include TERR: The Tibco Enterprise Runtime for R. TERR is a closed-source reimplementation of the R language engine, and not based on the GPL-licensed R project from the R Foundation. Here's the relevant slide from the webinar:

By making the TERR engine TIBCO intellectual property (IP), rather than using the open-source R engine, TIBCO claimed in the webinar to have been able to improve performance. Apparently, while some packages will run at about the same speed, others may run at 10x speed or even faster. This performance comes at the expense of compatibility: not all R functions or CRAN packages will work with the TERR engine, and it's not clear whether or at what rate TERR will follow R's development path.

The TERR engine will be included in the Spotfire Professional Client, and some new statistical interfaces (point-and-click regression and classification modeling dialogs) will make use of the engine. But if you want to use TERR-compatible R code in the Spotfire Web Player (to deploy beyond the local desktop), you'll also need a license for Spotfire Statistics Services.

Coinceidentally, a second enterprise analytics vendor also announced integration with R today. Teradata's Big Data Appliance, which combines high-performance hardware with open-source Hadoop and Teradata Aster software, will include integration between the Hadoop engine and R. From the data sheet:

The SQL-MapReduce framework, created by Teradata Aster, allows developers to write powerful and highly expressive SQL-MapReduce functions in languages such as Java, c#, Python, c++, and R, and push them into the discovery platform for advanced in-database analytics.

Like the similar RHadoop project, Teradata's R integration works with the open-source R engine.

The fact that more enterprise software vendors are integrating with R is generally a good thing for the R community: it validates the power of R within organizations, and adds more options for bringing advanced analytical methods developed in R to production environments. I just hope that the introduction of a prorpietary R language engine doesn't promote the fracturing of the vibrant R community — one of R's greatest strengths — and result in a fork of the R language into incompatible dialects.