RE:spark, we're curious about Ray mostly because of the potential for interactive-time (ms-level) compute for powering user-facing software. RE:dask, we care th

RE:spark, we're curious about Ray mostly because of the potential for interactive-time (ms-level) compute for powering user-facing software. RE:dask, we care that Ray interops with the rest of our stack (Arrow). I haven't evaluated Ray-on-pandas, and the Ray was previously focused on powering traditional ML, so again, just first blush on the announce. I don't think anything is inherent, more about priorities and momentum. For example, Spark devs have been working on cutting latency, and Conda Inc is/was contributing to the Arrow world. I had assumed the pygdf project would get to accelerating arrow dataframe compute before others, so this announce was a pleasant surprise!