A quick and dirty list….
1) Revolution R – http://www.revolutionanalytics.com/products/revolution-r.php Revolution R Community is Revolution Analytics’ free distribution of the open source R programming language — enhanced for users looking for faster performance and greater stability. It’s perfect for learning R and basic analysis
2) Oracle Enterprise R http://www.oracle.com/us/corporate/features/features-oracle-r-enterprise-498732.html
|Integrates the Open-Source Statistical Environment R with Oracle Database 11g
Oracle R Enterprise allows analysts and statisticians to run existing R applications and use the R client directly against data stored in Oracle Database 11g—vastly increasing scalability, performance and security. The combination of Oracle Database 11g and R delivers an enterprise-ready, deeply integrated environment for advanced analytics. Users can also use analytical sandboxes, where they can analyze data and develop R scripts for deployment while results stay managed inside Oracle Database.
3) Tibco Enterprise Runtime for R
TERR, a key component of Spotfire Predictive Analytics, is an enterprise-grade analytic engine that TIBCO has built from the ground up to be fully compatible with the R language, leveraging our long-time expertise in the closely related S+ analytic engine. This allows customers to continue to develop in open source R, but to then integrate and deploy their R code on a commercially-supported and robust platform—without the need to rewrite their code.
Prototypes are often developed in R, but then typically re-implemented in another language for production purposes because R was not built for enterprise usage. TERR brings enterprise-class scalability and stability to the agile R-language, and enables statisticians to broadly share their analyses through TIBCO Spotfire Statistics Services or by directly embedding the TERR engine.
4) pqR -http://radfordneal.github.io/pqR/ You gotta love Radford Neal’s throwing down the gauntlets to the old sleepy heads! At JSM , Montreal the R Core member announced they have agreed to incorporate his changes, signalling a major departure in the way changes have been signaled at R.
pqR is a new version of the R interpreter. It is based on R-2.15.0, distributed by the R Core Team (at r-project.org), but improves on it in many ways, mostly ways that speed it up, but also by implementing some new features and fixing some bugs.
One notable improvement is that pqR is able to do some numeric computations in parallel with each other, and with other operations of the interpreter, on systems with multiple processors or processor cores.
5) Renjin http://www.renjin.org/ Renjin is a JVM-based interpreter for the R language for statistical computing Renjin is a new implementation of the R language and environment for the Java Virtual Machine (JVM), whose goal is to enable transparent analysis of big data sets and seamless integration with other enterprise systems such as databases and application servers.
Renjin is still under development, with a target of a version “1.0” in late 2013, but in the meantime it is being used in production for a number of our client projects, and supports most CRAN packages, including some with C/Fortran dependencies.
6) Riposte (?) https://github.com/jtalbot/riposte
Riposte, a fast interpreter and JIT for R.
Justin Talbot email@example.com Zach Devito
We only do development on OSX and Linux. It’s unlikely that our JIT will work on Windows.
Planned work for July-December 2013. The first three bullet points are currently in progress on the library branch. Partial work will be integrated to main by the end of July.
- [x] Load the standard base R library without errors
- This will require support for about 15 primitive and external functions
- [ ] Support all R primitive operators (~200, 50 supported as of July 2013)
- [x] The most common 40 or so will be appear as bytecodes in the Riposte VM, primarily control flow operators and a small set of common arithmetic
- [ ] The rest will be implemented in the Riposte core library
- [x] Implement new .Map, .Scan, or .Fold FFI functions to allow vector fusion through primitives implemented as external calls in the core library
- [ ] Support for the 200 most common internal functions (out of ~580, 30 supported as of July 2013)
SAP , IBM Netezza already have specialized packages for R.
The question is SAS which supports interaction with R through SAS/IML, even Base R, and JMP- can it be willing to go the extra mile for customers and create SAS/R . The fact that they made their products compatible with R shows they acknowledge and respect R’s appeal ( contrary to old sleepyheads who think all SAS is good and all base R is divine)
SAS/ R can be the third major product for the SAS Institute after SAS and JMP platforms. Any takers, ladies and gentlemen?