Dataverse: SSIS vs. ExecuteMultipleRequest

The text discusses the comparison between ExecuteMultipleRequest vs. SSIS (SQL Server Integration Services) for processing large data on the Microsoft Dataverse platform. Emphasis is placed on the speed of data processing. SSIS is used with the KingswaySoft integration toolkit. A scenario is described where Contact records (88606) are retrieved and a Demo record is subsequently created based on this data.

• The SSIS process involves the creation of a Data Flow task, the addition of Dynamics CRM Source, then Dynamics CRM Destination with corresponding configurations and column mappings. The result showed that 88606 records were processed within 14 minutes and 37.640 seconds.

• Next, the ExecuteMultipleRequest method is tested which involved retrieving paging and implementation of large data. A detailed list of numbered codes (1 to 104) were shown suggesting the specific steps or codes to be used for this method.

Detailed Analysis

The comparison highlights the utility of SSIS and ExecuteMultipleRequest in processing large data sets. While SSIS presents an easy approach with use of the KingswaySoft toolkit, ExecuteMultipleRequest presents an alternative technique. Both are beneficial for complex data operations in Dynamics CRM, Model Driven Apps, the power platform, and other Microsoft applications. Performing such comparisons help evaluate and decide the most efficient technique based on the data type and volume, thereby enhancing data management and processing capabilities.

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Learn about Dataverse: SSIS vs. ExecuteMultipleRequest

Dataverse is a powerful tool for managing large data sets. There are two main methods for processing data in Dataverse: SSIS and ExecuteMultipleRequest. SSIS is a popular integration tool for data processing that can quickly process large data sets. In contrast, ExecuteMultipleRequest allows for a more efficient way to process large data sets. In this article, we will compare the two methods and learn how to use them for data processing.

First, we will look at how to use SSIS for data processing. For this example, we will be using KingswaySoft for the SSIS Integration toolkit. To start, we need to create a Data Flow task and add a Dynamics CRM source. Then, we can add a Dynamics CRM Destination with the appropriate configuration. After that, we need to configure the Columns mapping and run the task on our local machine. Once the task is complete, we can review the results to see how long it took to process the data.

Next, we will compare the use of ExecuteMultipleRequest. This method is more efficient for large data sets and can be implemented using the best practices outlined by Mark Carrington. This method combines retrieve paging with the ExecuteMultipleRequest and can be done using Microsoft Extensions Configuration, PowerPlatform Dataverse Client, XRM SDK, and other tools. Once implemented, we can compare the speed of processing the data to the SSIS method.

Finally, we can compare the two methods to determine which is better suited for our needs. Depending on the size of the data set and how quickly it needs to be processed, we can make an informed decision on which method to use for data processing. Both SSIS and ExecuteMultipleRequest provide powerful ways to process large data sets, and understanding the differences can help us make the best decision for our projects.

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Keywords

microsoft ssis, executeMultipleRequest, dataverse, Dynamics CRM CE, Model Driven Apps, KingswaySoft, Power Platform, Azure, Microsoft MVP, Dynamics CRM, Dynamics CRM Source, Dynamics CRM Destination, ExecuteMultipleRequest, Contact records, SSIS Integration toolkit