Altova MapForce Server
데이터 통합 작업의 고속 자동화.
Altova사에서 공개
2004년 부터 ComponentSource에서 판매중
가격: ₩ 1,227,600 버젼: 2023 Release 2 NEW 업데이스 날짜: Apr 12, 2023
데이터 통합 작업의 고속 자동화.
Altova MapForce Server performs data transformations for any combination of XML, JSON, database, EDI, XBRL, flat file, Excel, and/or Web service based on optimized data mappings.
Altova MapForce Server Features
MapForce Server Highlights
MapForce Server and MapForce
Altova MapForce Server includes the built-in data transformation engine developed for MapForce and is greatly enhanced to operate in server environments. MapForce Server performs data transformations for any combination of XML, database, EDI, XBRL, flat file, Excel, JSON, and/or Web service using preprocessed and optimized data mappings stored in execution files based on data mappings defined in MapForce. MapForce Server takes data transformation to the next level with server capabilities including parallel processing and multi-threading, bulk SQL merge, cross-platform support, and more.
Preprocessing enables faster performance and reduced memory footprint for most data mappings. MapForce Server operates under the management of FlowForce Server, in a standalone configuration executed from a command line, or programmatically via an API.
After a MapForce mapping is designed and tested, it can be executed by MapForce Server to automate business processes that require repetitive data transformations.
MapForce pre-processes and optimizes data mappings, stores them in MapForce Server Execution files for command-line execution by MapForce Server, and uploads them for use in FlowForce Server jobs.
Integration of Altova Server Products
MapForce Server may be configured with or without FlowForce Server, RaptorXML Server, or StyleVision Server, depending on the needs of your enterprise. For the most cost-effective solution, choose only the specific products you need. If needs change in the future, you can add other server modules. Each server is an independent product, licensed separately.
When MapForce Server operates under the management of FlowForce Server, data mappings are executed as FlowForce Server job steps, based on triggers defined as part of the FlowForce Server job.
FlowForce Server jobs can be triggered at specific time or time interval, or based on an event such as the arrival of a new file in a watched folder. For example, a new XBRL instance document lands in a directory, which triggers a multi-step FlowForce Server job to first validate the file using RaptorXML+XBRL Server, then execute MapForce Server to extract certain data from the XBRL and insert it into a database.
API for Direct Execution
MapForce Server includes an API that allows direct native execution by programs written in C# and VB.NET in Windows, from other Windows apps via a COM interface, and from Java programs in Windows, Linux, and MacOS.
This API allows developers to incorporate MapForce Server functionality as a feature of their own applications. One use case could be for MapForce Server to transform data coming from an external source to a standard internal format before a developer manipulates it in his own program.
API Code Examples
The documentation provided with the MapForce Server API contains code examples for C#, C++, Java, VBScript, and Visual Basic to help developers quickly access MapForce Server programmatically from .NET, Java, or COM-based code. The sample for C# is shown at left.
MapForce Server Supports Bulk Insert for Databases
Bulk Insert is an operation available for certain databases that allows a large volume of data to be inserted into a database table in a single SQL statement, as opposed to the typical method of using individual Insert statements for each row. Since processing overhead by the database engine is greatly reduced, performance is much faster. Testing MapForce Server with some examples has shown Bulk Insert can be more than 10 times faster than individual Insert statements.
Bulk Insert is also advantageous in multi-user environments. A long series of Insert commands transmitted to the database by one user could potentially be interrupted by another user sending a Select request to the same table, then the Insert sequence would continue. In a situation like this the Select operation would result in incomplete or invalid data.
MapForce Server Advanced Edition