When the dataflow runs through asynchronous steps, each step may perform different things with different speed. In this setting, Back-pressure means a fast producer and slow consumer.
If the producer and the consumer writes/read on disk, there is no backpressure problem
The issue of back-pressure comes when your consumer is not capable of processing income data in the same rate.
A streaming software will be implemented in this case in order to:
The longer a consumer stay offline the higher will be the back-pressure.
To avoid overwhelming such steps, which usually would manifest itself as increased memory usage due to temporary buffering or the need for skipping/dropping data, so-called backpressure is applied,
Backpressure:
This allows constraining the memory usage of the dataflows in situations where there is generally no way for a step to know how many items the upstream will send to it.