My current thinking is that it would make sense to implement the standard DataFrame abstraction (with all the generic functionality it offers) with a couple kinds of distributed data frame. One approach is to make a distributed stack of local data frames; another is to make a single data frame where each column is a distributed vector. Not sure which is better. Fortunately, Julia makes it really easy to experiment with these kinds of things. Of course, as soon as you have a system like that you need a scheduler for work at which point you want something like Dask or Dagger (https://github.com/JuliaParallel/Dagger.jl).