When growing capacity and power in the data center, the architectural trade-offs between server scale-up vs. scale-out continue to be debated. Both approaches are valid: scale-out adds multiple, smaller servers running in a distributed computing model, while scale-up adds fewer, more powerful servers that are capable of running larger workloads. It’s worth noting that there are additional, unique advantages that scale-up architectures offer. One big advantage is large memory and compute capacity that makes In-Memory Computing possible. This means that large databases can now reside entirely in memory, boosting the analytics performance as well as speeding up transaction processing. By virtually eliminating disk accesses, database query times can be shortened by many orders of magnitude, leading to real-time analytics for greater business productivity, converting wait time to work time.