MapForce Server is an enterprise software solution that runs data mapping transformations on Windows, Linux, and macOS operating systems. The data mappings themselves (or Mapping Design Files, *.mfd) are visually designed with Altova MapForce ( https://www.altova.com/mapforce ), where you define the inputs, outputs, and any intermediary processing steps that must be applied to your data. The role of MapForce Server is to run MapForce Server Execution (.mfx) files compiled with MapForce, and to produce the output files or data, or even update databases or call Web services, according to the design of the underlying mapping.
MapForce Server can run standalone as well as under the management of Altova FlowForce Server ( https://www.altova.com/flowforceserver ). When installed on the same machine as MapForce Server, FlowForce Server automates execution of mappings through scheduled or trigger-based jobs, which can also be exposed as Web services. In addition to this, FlowForce Server includes a built-in library of functions that enable you to take additional automated actions before or after mapping execution, such as sending email, copying files and directories, uploading files to FTP, running shell commands, and others.
•Server-level performance when executing data mappings
•Cross-platform: MapForce Server runs on Windows, Linux, or macOS operating systems
•Command line interface
•An API that you can call from C++, C#, Java, VB.NET, VBScript, or VBA code
•Native integration with FlowForce Server
•Support for Altova Global Resources—a way of making file, folder, or database references configurable and portable across multiple environments and across multiple Altova applications, see Altova Global Resources
•Runs mappings that read data from and write data to Protocol Buffers binary format
•Runs mappings that perform bulk database inserts
•XML digital signatures are not supported
•ADO, ADO.NET, and ODBC database connections are supported only on Windows. On Linux and macOS, native database connectivity is available for SQLite and PostgreSQL databases. For other databases running on Linux or macOS, JDBC should be used.
Last updated: 27 September 2019