What distinguishes threads in the processing model of batch jobs in MuleSoft?

Threads in the processing model of batch jobs in MuleSoft are primarily designed to improve performance by allowing multiple records to be processed simultaneously. This concurrent processing capability enables batch jobs to handle large volumes of data more efficiently, thereby reducing the overall execution time.

When batch jobs leverage multithreading, different threads can operate independently on separate records, effectively utilizing available resources and enhancing throughput. This approach makes it possible to scale processing without requiring a linear increase in processing time as the number of records grows.

This functionality is critical in scenarios where high performance is essential, such as in data integration tasks where large datasets need to be processed quickly. By enabling threads to work in parallel, MuleSoft optimizes resource utilization and supports the execution of complex batch processes more effectively.