What is the processing style of batch integration?

The processing style of batch integration is characterized by the scheduled processing of data in bulk. This approach involves collecting a large set of data over a period of time and then processing that data all at once, rather than processing each individual record as it comes in. This method is particularly useful for large volumes of data that don't require immediate action, allowing organizations to manage resources more efficiently and optimize performance.

Batch integration is often used in scenarios such as data migration, synchronization of large datasets, or generating reports where immediate results are not critical. It can run during off-peak hours to minimize the load on systems and provide significant processing capabilities.

In contrast, immediate processing refers to handling data as it arrives, which is characteristic of real-time integration. Stand-alone integration without server interaction suggests a lack of connectivity or data processing capability, which is not in line with how batch integration operates, as it typically involves interaction with databases or servers to manage the bulk data being processed.