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  • What's New in Spotfire® 10.10 LTS

    Message added by Surbhi Khimesra,

    this article is kept for reference but some of the links may be broken due to Spotfire systems being updated over the years, please post a question in our Forum or submit a support ticket if you need any assistance with an older Spotfire version that is still supported


    Spotfire 10.10 LTS is a Spotfire Long-Term Support release and also introduces support for Python data functions in Spotfire web clients and Automation Services, data connectivity to SharePoint Online Lists and new styling options for tables and cross-tables. This release includes a new version of TIBCO Enterprise Runtime for R (TERR).

    Also available in Spotfire 10.10 LTS are a number of ease of use enhancements including adding comments in expressions, easier management for add row recommendations, data transformation indications in the data canvas, ability to duplicate a map chart layer in another map chart and ability to maximize custom expression editor and other dialogs. On the data connectivity side, users will benefit from features and improvements related to SAP BW, Teradata Vantage, Cloudera Data Platform and IBM Netezza.

    Administrators will find an extended list of PostgreSQL databases now supported as Spotfire database.

    Developers get access to new APIs to customize Spotfire's top level menu and to use the current Spotfire's theme in their custom export tools.

    Data Access

    SharePoint Online Lists support

    With this new Spotfire connector you can login directly to your SharePoint Online instance, browse and select SharePoint Lists and instantly load list content into Spotfire as data tables.



    After authenticating using the web browser you can select sites and sub-sites and even add additional sites manually.



    It's easy to search and select data from lists. Notice that metadata columns are not selected by default since there can be quite many of them.


    SAP BW display attributes Support

    You can now bring in display attributes together with SAP BW characteristics into your Spotfire analysis. Together with the short, medium and long descriptions, this extends the range of possible analytic use cases for Spotfire on SAP BW.



    Display attributes are configured for each characteristic in the rightmost settings panel.


    Teradata Vantage 2.0 support

    The TIBCO Spotfire connector for Teradata now supports Teradata Vantage 2.0 and Native Object Store (NOS). This means that you can run Spotfire analytics on Teradata Vantage and query, for example, Amazon S3 and Azure Blob directly. This enables you to join data lake file-based tables with traditional tables in Teradata. This makes it easy for Spotfire users to create views and joins across all their data and, with a few clicks, be prepared for visual data discovery.

    Edit data source server field while keeping entered username and password

    Sometimes you realize that Spotfire fails to connect because the address to the data source is wrong. For example, maybe a port number needs to be added after the IP address because the data source is not using the default port. You can now make changes like this in the server text field without entering the username and password again.

    You will benefit from this enhancement in the following connectors:

    1. Apache Spark SQL
    2. Amazon Redshift
    3. Cloudera Hive
    4. Essbase
    5. Greenplum
    6. PostgreSQL



    Notice that you can edit the server details while keeping the username and password fields information.


    Cloudera Data Platform (CDP) Cloud Impala and https transport protocol support

    The TIBCO Spotfire Connector for Cloudera Impala now supports CDP Cloud Impala. This is enabled by the added support for the http transport protocol, which is required to connect to CDP Cloud.



    Notice the new transport mode selector and path field.


    IBM Netezza Performance Server support

    The TIBCO Spotfire Connector for IBM Netezza has been upgraded and verified to support the next step in the evolution of Netezza, IBM Performance Server (IPS), sometimes referred to as Netezza v11.

    Data Wrangling

    Comments in expressions

    It's now possible to add comments to custom expressions. This makes it easier to understand and maintain complex custom expressions.



    Easier to view, apply and ignore add rows recommendations

    Based on Spotfire X feedback, we have made several enhancements to the user experience when adding data (the summary view). For example, it's now easier to view, apply and ignore recommendations on how to add your data. It's also easier to know that the white box representing a data source can be expanded to reveal more options.



    You now have the option to skip one or all recommendations in the summary view. The new arrows make it easier to know that more options are available.

    If you opt out of a recommendation, the data will automatically be configured to be added as separate data tables.

    If you are a Spotfire Analyst user, you can remove all recommendations on how to add data from the Tools > Options ? Document page, and an administrator can, using the Administration Manager, under Application Preferences, change the DataImport preference AllowAddDataRecommendations for a group of users.



    Multi-select column matches/data table relationships

    Many column matches are automatically created. For wide data sets, there could be a lot of them. However, until now you couldn't easily remove them because you had to select each one individually. You can now multi-select column matches and relations by using the mouse in combination with the Shift and/or Ctrl key. Once selected, you can quickly delete the matches or relations by clicking the Delete button.




    Data canvas indication of which columns and rows were added by data transformations

    The data canvas makes it easy to see which added rows, added columns and calculated columns that are included in a Spotfire final data table. If you select a data transformation in the graphical view, and you are viewing the Data tab in the lower right part of the data canvas, you will now see that Spotfire automatically scrolls to and highlights the selected transformation's added rows, added columns or calculated columns, respectively. This makes it easier to navigate and review row or column level details.

    Visual Analytics

    Background and text color in tables

    You can now configure the color of the cell background and the text in table visualizations.


    Colors can be applied to the header and/or the data values, and can be set for all columns or selected columns, respectively.

    This allows creation of more readable and visually appealing tables and also allows highlighting of certain aspects of the data.




    Background and text color in cross tables

    The color of the cell background and the text in cross table visualizations can now be configured. The color can be applied to both vertical and horizontal headers as well as to data values, and can be configured for all or individual columns or rows. 

    This allows creation of more visually appealing and readable cross tables and also allows highlighting of certain aspects of the data.




    Add layer from another Map chart

    You can now add a layer to a map chart by duplicating an existing layer from another map chart in your analysis.


    Maximize button on custom expression editor and other dialogs

    The custom expression editor and many other dialogs in the installed client now have a maximize button to make it quicker to use all the screen estate to view the contents of the dialog. The following dialogs now have a maximize button:

    • Custom expression dialog (also in the context of data transformations and calculated columns)
    • Data function script dialog
    • Administration manager
    • Library administration
    • Folder permissions on library administration
    • Edit SQL in Information Designer
    • Edit HTML in Edit text area
    • Manage data connections

    Advanced Analytics

    Python data functions in Spotfire web clients and Automation Services

    In Spotfire 10.10, Python data functions can be used in the web clients and in Automation Services jobs, using the new TIBCO Spotfire® Service for Python.

    This means that it's now easier to deploy advanced analytics powered by the Python data science ecosystem to a large number of users through the Spotfire web clients, and it's possible to use Python data functions also in automated jobs using Spotfire Automation Services.

    This is enabled by the new Python Service, shown in the Spotfire environments architecture in the picture below.


    Just as the existing TERR Service, the Python service runs on a node in the Spotfire environment, behind the Spotfire Server from the client's perspective. The Python service, just like the TERR Service, is packaged with TIBCO Spotfire Statistics Services.

    Improved management of R and Python packages - manage multiple .SPK files containing R and Python packages using the Spotfire Server

    Using TERR or the Spotfire Python package builder, it is possible to pack R/Python packages into an .SPK file and have it distributed to Spotfire clients with the Spotfire Server's package deployment mechanism, which is good for governance related to the R/Python packages used in an organization. In Spotfire 10.10, it is possible to deploy multiple .SPK files to a deployment area, and let the clients receive all of them. There was previously a limit of one such .SPK file per deployment area. This makes it easier to manage the R/Python packages used in the organization in general, and especially when there are multiple organizations that provide R/Python packages to be distributed to end users, such as in OEM use cases.

    TIBCO Enterprise Runtime for R 5.1

    Spotfire 10.10 includes a new version of the commercially supported implementation of the R language, TIBCO Enterprise Runtime for R, abbreviated TERR.

    Save an SBDF file to the Spotfire library directly from TERR

    TERR now has the capability to save an SBDF file directly to the Spotfire library. This is helpful when you want to share the data produced by a TERR job, like when using the data in more than one analysis file.

    Check this example on TIBCO Community and see more details in the documentation.

    Compatibility with Open Source R packages on CRAN

    In TERR 5.1 the compatibility with R packages on CRAN have been improved. For detailed test results see the TERR documentation site.

    R packages available on TIBCO Cloud

    For TIBCO Cloud Spotfire users there are three new packages available; cartogram, EpiEstim and EpiModel.

    Note: To keep in synch with the CRAN package repository, 11 packages that have been removed on CRAN have also been removed on TIBCO Cloud Spotfire: bclust, bisoreg, DPpackage, geoRglm, growcurves, MasterBayes, maxent, profdpm, RArcInfo, RJaCGH, rPython, RTextTools, XLConnectJars.

    Server and Administration

    Amazon Aurora for PostgreSQL is supported as Spotfire database

    Amazon Aurora with PostgreSQL compatibility is supported as the configuration database for the Spotfire Server. Amazon Aurora is a fully managed relational database that is compatible with PostgreSQL.

    Amazon RDS for PostgreSQL is supported as Spotfire database

    Amazon RDS for PostgreSQL is supported as the configuration database for the Spotfire Server. Amazon RDS for PostgreSQL is a fully managed relational database for PostgreSQL in AWS.

    Amazon RDS supports PostgreSQL major version 11.

    Azure Database for PostgreSQL is supported as Spotfire database

    Azure Database for PostgreSQL is supported as the configuration database for the Spotfire Server. Azure Database for PostgreSQL is a fully managed relational database for PostgreSQL in Azure.

    Azure Database supports different PostgreSQL versions.

    Google Cloud SQL for PostgreSQL is supported as Spotfire database

    Google Cloud SQL for PostgreSQL is supported as the configuration database for the Spotfire Server. Google Cloud SQL for PostgreSQL is a fully managed relational database for PostgreSQL in Google Cloud.

    Google Cloud SQL supports different PostgreSQL versions.

    SQL Server 2009 and 2017 for Linux supported as Spotfire Server DB

    Microsoft SQL Server 2019 and Microsoft SQL Server 2017 for Linux are supported as the configuration database for the Spotfire Server. This is in addition to the existing support of the same database versions for Windows.

    Microsoft SQL Server 2019 (15.x) is the latest public release of SQL Server. For more information see SQL Server 2019 Release Notes.


    Microsoft SQL Server 2017 is the previous public release of SQL Server. For more information see SQL Server 2017 Release Notes.

    Spotfire Server, Node Manager and Statistics Services upgraded to Java 11

    The Spotfire Server, Node Manager and Statistics Services now use Java 11 instead of Java 8.


    Java 11 is the latest long-term support (LTS) version. The Oracle Java SE distribution is included in the Spotfire Server and node manager packages.

    For a complete list of changes, see the OpenJDK JDK11 Feature List (Java 11 reference implementation) and the Oracle JDK 11 Release Notes (the Oracle OpenJDK specific distribution).

    Centos 8 supported for Spotfire Server, TERR Service, Python Service and Statistics Service

    CentOS Linux 8 is supported as Operating System for Spotfire Server, TERR Service and Statistics service.

    CentOS Linux is the Community Development Platform for the Red Hat family of Linux distributions.

    CentOS Linux 8 is the latest stable version and was released on 2019-09-24.

    Improved performance when saving analysis files

    The performance has been improved when saving a dxp file to a remote server, such as a shared drive on the network.


    The time savings are most noticeable in cases when the WebDav protocol is used.

    APIs / SDK

    Custom top level menus

    You can now use the C# API to add new top level menus for your custom application and document tools. A custom top level menu can also contain sub menus for more fine-grained arrangement.

    This is especially useful when using Spotfire as a platform to build analytic applications. Since custom tools are often the most used tools for users of an analytic application, having direct access to them in a top level menu makes the analytic application easier to use. In addition to the existing custom toolbar, co-branding and white-labeling capabilities, the top level menus feature provides an extra option for customizing Spotfire. Read more here.




    Custom Export Tool with current theme

    With this release it is possible to have a Custom Export Tool to follow the current theme that is used in the analysis, in addition to using the Spotfire light theme (default). This affects not only colors, but also layout, such as font sizes, etc.

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