I don't think that there's a "win" here. It's just sort of which way you tilt your head, how much space do you have to cram a ton of cores connected to a really wide memory bus and how close can you get the storage while keeping everything from catching on fire, no? ("just sort of" is going to have to skip leg day because of the herculean lift it just did)

It's a fairly fractal pattern in distributing computing. Move the high throughput heavy computation bits away from the low latency responsive bits ("low latency" here is relative to the total computation). Use an event loop for the reactive bits. Eventually someone will invert the event loop to use coroutines so everything looks synchronous (Go, anyone? python's gevent?).

After it seems to me that the only real question is if takes too long or costs too much to move the data to the storage location the heavy computation hardware uses. There's really not much of a conceptual difference between airflow driving snowflake and c++ running on a cpu driving cuda kernels. It takes a certain scale to make going from a OLTP database to an OLAP database worth it, just like it takes a certain scale to make a GPU worth it over simd instructions on the local processor.