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Analytic Development Languages Supported by TIBCO Data Science

Last updated:
1:54pm Jun 28, 2021

TIBCO provides data science for everyone: Data Scientists, Data Engineers, Developers, and so on. However, each of these roles has different preferences and requirements for how to do data science, including the choice of the development environment and the coding languages. Fortunately, TIBCO Data Science (a single, unified platform for creating and operationalizing data science) can handle most preferences, technologies, and languages. Here is a list that organizes them, with links to tips & tricks elsewhere in the Community to help you.

Development Scripting Languages and Custom Extensions

R, Python, Scala, Java, C#, C, SQL, MDX, Pig, Hive QL, Spark

TIBCO Data Science tools offer a wide range of native features and possibilities where a user does not need coding at all. Nevertheless, in addition to no code options there is  also possibility to use other scripting languages for implementing data science computations. TIBCO Data Science tools typically use nodes/operators (basic elements from which the analytical process is built) as part of their graphical workflows where a user can incorporate code from various scripting languages. During the runtime, such node/operator executes the code according to the type of code (e.g. call another execution environment) and typically brings back the results which can be utilized in further analysis by consequent nodes/operators. An example of such a workflow is shown below.

Deployment (Code Generation Languages)

Predictive models generated in C, C++, C#, Java, PMML, PFA, SAS, SQL Stored Procedure in C#, SQL User Defined Function in C#, Statistica Visual Basic

Once the predictive modeling is done, tools can produce a code of the model which can be afterward used for further scoring  in TIBCO Data Science platform itself or in other applications (deployment environments, real-time scoring engines, or even gateways).  

Execution Environments

TIBCO Data Science tools can use and invoke as part of the computational process following environments:

TERR, R, Python, SAS, MatLab, most RDBMS, most flavors of Hadoop, Hive, Spark, Flogo

Analytic Market Places

Azure ML, AWS, Apervita, Algorithmia, H20, Microsoft CNTK, TIBCO Community Exchange

External models, methods, and know-how can be also taken from external sources like marketplaces. Again, you can use nodes in your analytical workflow to invoke and use information from an external source. Such nodes can be a model, a single method, or an entire analytical procedure. All of this is combined inside a single processing environment of TIBCO Data Science.



You can find some of the references connected with the topic below: 

  • (videodocumentation) Open source integration in Statistica
  • (documentation) Jupyter Notebooks
  • (documentation) Custom operators in Spotfire Data Science
  • (documentation) SQL Execute operator in Spotfire Data Science
  • (documentation) Pig Execute operator in Spotfire Data Science
  • (documentation) HQL Execute operator in Spotfire Data Science
  • (video) Model deployment
  • (documentation) Model export formats in Spotfire Data Science
  • (video, blog) Edge scoring - Flogo IoT example
  • (wiki) Matlab integration 
  • (video) H2O and other marketplaces connection with Statistica
  • (video) Spart integration with Statistica
  • (videowiki) Integration with analytic marketplaces
  • (wiki) Deep learning through Microsoft Cognitive Toolkit
  • (exchange) TIBCO Community Exchange templates and extensions

Using development scripting languages directly from TIBCO Spotfire:

  • (wiki) TERR data function
  • (wiki) Statistica data function
  • (wiki) Python data function


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Feedback (1)

If we have in addition TIBCO Data Virtualization in our solution we can use the following programming and query languages: XSLT, XQUERY, XPATH, SQL, MDX, HiveQL and TDV scripting language. TIBCO Data Virtualization can be accessed from any component of TIBCO Data Science solution. 

Tomáš Jurczyk 5:49am Oct. 24, 2018