Many modern performant solutions will use both, but they're not the same thing.
Mass storage is most efficient when doing large sequential reads and writes, so you normally feed your constant-space streaming algorithms from buffers with a large number of input records.
Sometimes you can just tell the OS do efficient chunking prefetch for you.
The hard part for me is the "transpose" or "striding" problem. i.e. when the data is stored in a series of (x, y, z) files for a given hour, day, or month and I need a time series at a point.
If your intended audience are data scientists then why didn’t you mention Dask?