Hyperscalers and the academics that often do work with them have invented a slew of distributed computing methods and frameworks to get around the problem of scaling up shared memory systems based on symmetric multiprocessing (SMP) or non-uniform memory access (NUMA) techniques that have been in the systems market for decades. SMP and NUMA systems are expensive and they do not scale to hundreds or thousands of nodes, much less the tens of thousands of nodes that hyperscalers require to support their data processing needs.
It sure would be convenient if they did. But for those who are not hyperscalers, …
In-Memory Breathes New Life Into NUMA was written by Timothy Prickett Morgan at The Next Platform.