Very few data processing activities are bottlenecked by single thread performance. Similarly as memory, thread count, and storage capacities of modern servers have continued Moore's law the number of applications that can fit within the same finite cost has also improved.
In terms of efficiency, the big question is "does an incremental gain in efficiency matter for this application?" if we're talking about < 10x performance/cost change the answer will be no for most teams. Consider how many of these big data applications are implemented in python or other interpreted languages.
In terms of efficiency, the big question is "does an incremental gain in efficiency matter for this application?" if we're talking about < 10x performance/cost change the answer will be no for most teams. Consider how many of these big data applications are implemented in python or other interpreted languages.