TIBCO Enterprise Runtime for R

TIBCO Enterprise Runtime for R is a high-performance, enterprise-quality statistical engine. Brings speed, reliability and support to open-source R code – Enterprise R.

From A$9,800/processor/year +gst
(Contact us for US$ price)

TIBCO Enterprise Runtime for R Console

 Develop in R and deploy on TIBCO Enterprise Runtime for R. Accelerate prototyping to production, without recoding. Integrate predictive analytics consistently across the organization.

TIBCO Enterprise Runtime for R Licenses

TIBCO Enterprise Runtime for R (TERR) provides a completely new statistical engine, based on TIBCO’s extensive expertise as the developers of S+.

TERR is not open source/ GPL, and can be licensed for embedding in applications and redistribution

The console provides a simple interface for sending commands and executing scripts.

Fast performance and highly efficient memory management to optimize your R analyses. As the image suggests, the system time for generating random variables in TERR vs R is mush faster.

TERR Advantages

High-performance and robust memory management for maximum reliability and superior handling of large datasets than open source R.

Future-proof, robust, modern architecture for today and tomorrow’s customization needs.

Broad coverage of core R functionality and compatibility with CRAN packages.

TERR is embedded with Spotfire.

Feature List

Not open source/ GPL

  • Can be licensed for commercial embedding and redistribution.
  • Integrate in custom applications via a variety of APIs

Existing R code runs faster and more reliably

  • Combining an enterprise-grade engine with superior performance and memory management, and compatibility with thousands of R packages, TERR can run your existing scripts better and faster

Fast prototyping to production

  • TERR provides a robust platform for the R language integrated into data discovery, business intelligence, and real-time applications so you can quickly develop new analytic methods and deploy them to production—without the delay and expense of rewriting and retesting them in a new environment

Simpler and faster big data processing

  • TERR superior memory management and 64-bit architecture enables far larger data sets to be handled in memory, simplifying big data processing. For even bigger problems, integration with big data frameworks such as Hadoop, Spark, H2O, FuzzyLogix, and others, enable big problems to be solved more quickly and with fewer resources.
System Requirements
Processor8 Cores or more (Intel Xeon E5 or equivalent), 2 GHz or higher, 64-bit
(4 Cores (Intel Core i3 or equivalent), 2 GHz, 64-bit, minimum)
Note: The system default is one engine fewer than the number of cores. You can add cores to accommodate additional engines. You can add cores to accommodate additional engines. See TIBCO® Enterprise Runtime for R – Server Edition Installation and Administration
 for information about configuring engines.
RAM16GB or greater
(8GB RAM, minimum)
Note: The minimum amount of RAM is suitable for only basic test systems, or systems with very few simultaneous users. Production servers with large analyses or many simultaneous users require significantly more RAM. Contact TIBCO for further assistance with this.
Hard Disk25 GB
(12GB, minimum)
Operating SystemWindows Server 2019
Windows Server 2016
Windows Server 2012 R2
Windows Server 2012
Red Hat Enterprise Linux 8
Red Hat Enterprise Linux 7
Red Hat Enterprise Linux 6
SUSE Linux Enterprise Server 12
SUSE Linux Enterprise Server 11
Note: Only 64-bit versions of the operating systems are supported
Note: Containers are not supported.
TIBCO® Enterprise Runtime for R – Server Edition version 1.3.0Docker (Linux only) The service builds a default Docker image based on Centos 7, which is also available from Docker Hub. (The recommended Docker version, 17.12.1-ce, was tested with Centos 7.4 and higher.) 
You cannot modify the image we provide. You can provide another prebuilt image. 
Check Docker Hub for an image that might work for you.
TIBCO® Enterprise Runtime for R (TERR™)5.1.0