It is important to not conflate "massively parallel" (HPC) and "massively distributed" (Internet-scale), they have different architectural requirements and solve different classes of problem. People with competency in either of these areas tend to overestimate their understanding of the other but they are not solving the same computer science problems even though they look similar on the surface.
Massively distributed systems do not get much benefit from low-latency interconnects. Massively parallel systems do, and in particular, it is a "throw hardware at the problem" kind of solution that helps cover for the fact that virtually no software designers can engineer efficient, non-trivial, massively parallel systems. MapReduce is a distributed model; outside of some trivial cases, it is a poor parallel model. And while the HPC community has a much better understanding of massive parallelism than the Internet-scale systems community, the HPC community largely doesn't grok massively distributed systems in the way that someone working on Google's infrastructure would.
I benefitted from having spent several years designing software for both HPC and Internet-scale systems. They are not fungible, and both communities grok things that the other is oblivious to. Even within the HPC community though, the number of people skilled at the design of massively parallel software systems is quite small, much smaller than people that know massively distributed systems.
You do not need two systems, you need one system and more people that have figured out how to design massively parallel software -- the real problem. It is difficult to overstate just how rare this skill is even within the HPC community.