This is exactly the secret behind mainframe's ubiquitous persistence across mission-critical businesses. Consistency and availability are far more important than partition tolerance. You build your mainframe with >N+2 redundancy on any given component and then you build the datacenter around the mainframe. This is how you beat the CAP theorem. With brute-force engineering. Sure, you aren't truly defeating it in principle, but in practice it still seems to be the best option we've got.

Batch is the other aspect that takes mainframes to unbeatable status. When you run a batch job, you basically say "ok all daily OLTP is halted, we are going into a completely new architectural mode". Obtaining an exclusive lock on a table or an entire database for a single series of processes to operate on can yield insane amounts of throughput when you are finalizing the data from the day's operations.

A few years ago as a more junior developer, I will admit to being strongly "anti-mainframe" based on the principles I held at that time. Why can't we just put it all in the cloud, throw some MongoDB out there and pray it all works? After witnessing actual business cases for mainframe/batch unfold, I quickly started to change my tune. Mainframe is not for every business, but it does seem to be a tool you can reach for when someone says "everything just has to work always or someone dies", and "we have infinite money".

Is this built into the hardware then? Might you or someone else elaborate on how mainframe architecture provides for this level of CA?