MapForce supports mapping protocol buffers (Protobuf) to and from other structured data formats as mapping sources or targets. In the constant quest for more efficient ways to transfer, manipulate, and manage large structured data sets, Google has created a language- and platform-neutral data format similar to XML, but smaller, faster, and simpler than even JSON data. Tools are available to generate and work with Protobuf using Java, Python, C++, C#, Ruby, and other programming languages.
The structure of any Protobuf message is defined in a .proto file that defines each field name and value type. Altova MapForce lets users drop these .proto files into a data mapping as a source or target along with any other data, including XML, JSON, relational databases, Excel, flat files, REST and SOAP web services, and others. .proto files versions 2 and 3 are supported.
A MapForce data mapping creates compatibility between existing XML, JSON, database or legacy data formats and new applications leveraging the efficiency of Protobuf.

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New Features Increase Developer Productivity
The latest release of Altova desktop developer tools, server software, and regulatory solutions introduces a host of productivity-boosting features across the product line, as well as updated support for standards, databases, and integration with popular IDEs.
Let’s take a look at the highlights.
Mobile App Themes Improve User Satisfaction
Mobile app themes improve user satisfaction by letting each user customize the app appearance with personal preferences. One way to implement multiple themes in apps that report and visualize data is to offer users a choice of color palettes for charts and graphs. MobileTogether uses a combination of drag-and-drop UI design, the powerful Action Tree visual programming language for event handling, and standardized functional programming for data selection and processing. Developers use MobileTogether every day to create elegant cross-platform apps with rich charts and graphs in all popular formats.
The main chart configuration settings let mobile app developers choose any of four built-in color palettes or even define a custom color palette for charts and graphs as they design an app. Combined with dark mode and light mode display settings, that creates ten colorful possibilities for display customization. Rather than impose a design-time color choice, developers can leverage MobileTogether features to let users choose for themselves. Let’s look at an example.
Transforming and Converting Protobuf
MapForce supports mapping protocol buffers (Protobuf) to and from other structured data formats as mapping sources or targets. In the constant quest for more efficient ways to transfer, manipulate, and manage large structured data sets, Google has created a language- and platform-neutral data format similar to XML, but smaller, faster, and simpler than even JSON data. Tools are available to generate and work with Protobuf using Java, Python, C++, C#, Ruby, and other programming languages.
The structure of any Protobuf message is defined in a .proto file that defines each field name and value type. Altova MapForce lets users drop these .proto files into a data mapping as a source or target along with any other data, including XML, JSON, relational databases, Excel, flat files, REST and SOAP web services, and others. .proto files versions 2 and 3 are supported.
A MapForce data mapping creates compatibility between existing XML, JSON, database or legacy data formats and new applications leveraging the efficiency of Protobuf.
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Excel Data Mapping to Update Existing Documents
Excel began life as a simple spreadsheet tool. Over time, support for rich text styling options, built-in charts, and copy and paste formatting features has led many enterprises to create reports in Excel documents. This can cause difficulty when data changes and existing documents need to be manually updated for distribution to a wide audience in the familiar report style.
Altova MapForce, the award-winning, graphical data mapping tool for any-to-any conversion and integration, supports Excel data mapping to convert data to existing Excel documents while preserving styles and formulas in the original.
This feature lets you write directly to nicely formatted Excel files to update data at runtime: any designated worksheets, rows, and cells from the specified file will be replaced with data from the mapping and all formatting in the existing file will be preserved as-is. To protect functionality in the existing spreadsheet, cells with formulas are not overwritten.
Let’s look at an example of how to map Excel data.
How to Compare XML and Other Files
The ability to diff and merge files is a necessity for every developer. This can be especially troublesome when trying to compare differences between files containing structured data, such as XML.
The video tutorial below provides an explanation on how to compare XML files – and more – using both XMLSpy and DiffDog. These powerful utilities perform diff and merge operations in an XML-aware manner, which reduces the number of false positives seen when comparing files.
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XML Reports to Text
Creating business reports from data stored in XML and relational databases is a common requirement in most organizations. However, it’s often complicated by the need to have information available in both web formats and print-ready formats such as PDF. Altova StyleVision takes a unique approach to report creation by letting users design reports from XML, databases, and even XBRL in a visual way – and output them in multiple formats simultaneously.
Over the years, support has been added for output to HTML, RTF, Word, and PDF – and now, based on customer feedback and requests, StyleVision also supports direct output to text. Let’s take a look at how it works.
Data Mapping NoSQL Databases
NoSQL databases are non-tabular databases that store data differently than traditional databases made up of relational tables. Two of the most popular NoSQL databases, MongoDB and Apache CouchDB, store data as collections of BSON (binary JSON) and JSON documents. These databases leverage flexible JSON schemas and scale easily with large amounts of data and high user loads.
Altova MapForce has long supported data mapping all popular relational databases and now also includes native support for data mapping NoSQL databases. MapForce includes functionality for inserting, extracting, filtering, and ordering NoSQL data. Let’s look at an example.