spark and presto have big farms of workers. it's a replacement for the part that owns the memory where the computations happen on the workers. it has a handful

spark and presto have big farms of workers. it's a replacement for the part that owns the memory where the computations happen on the workers. it has a handful of fast support libraries and i/o libraries but can also make use of spark and presto. it is probably faster to start up and has less fixed overhead (beyond the space used by the work area) than the usual runtimes because it is written in c++. it also is probably a better bridge for dl type workloads. you can think of it as similar to a "python kernel" but distributed and language agnostic for "big data" type jobs.