Why isn't differential dataflow more popular?
Indirectly answering the question - I've skimmed through the git README, the abstract and all the pictures in the academic paper that it references.I have no idea what this thing does. Can someone explain in simple terms what it does?My organisation is currently investigating on installing Spark on the theory that it connects to databases and we need analytics. As far as I can tell it breaks analytics work into parallel workloads.[0] https://github.com/TimelyDataflow/differential-dataflow/