Also worth noting is that the implementation matters at least as much as the API.
In this case there are substantial differences: Data flow is a DSL, not a Java API, and it is designed for streaming data. It is unclear if Crunch handles the streaming case, but it talks a lot about Map/Reduce which makes me think it isn't the primary usecase.
those jump to mind, but I'm sure there are plenty of other overlaps in the Apache sphere. They certainly embrace it.
That's just plain dumb, since that word is used in so many other settings, especially big data settings (TensorFlow is also a dataflow system, but both the data types and model are completely different, etc.). So I can see why someone would just dismiss it as yet another framework, sort of like how all these JavaScript frameworks that are the hot thing one year and then legacy code the next.
If they had used a more specific name, I think it would help the perception a lot. The main point is batch vs streaming, which is still big pain point, and being precise about the event time vs event processing time.