Yes, I like how the paper is written, and the work is solid IMO, having used most of the predecessors. The annoying thing is footnote 1, where they explain that they coopted the term "dataflow model".

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.