In the area of data integration and middleware, distributed data processing systems create directed workflows to perform data cleansing, consolidation and calculations before emitting results to targets such as data warehouses. To provide fault tolerance, expensive system-wide checkpoints of distributed workflows want to be performed on the level of seconds while commits to transactional target resources must happen much more frequently to satisfy near real-time result latency [1] and small transaction size requirements. When there exists non-determinism in the workflow, the commit against a transactional target is allowed to be issued only when the determinants were saved to stable storage and deterministic replay can assure exactly-once result delivery. That is, there exists a dependency: the process q (a.k.a. operator or component in the context of data integration) executing the transaction is not allowed to make forward progress unless it has received the notification of the non-deterministic process p stating that the results to be committed can be replayed deterministically in the event of a crash.