  Along with today's data explosion and application diversification, a variety
of hardware platforms for big data are emerging, attracting interests from both
industry and academia. The existing hardware platforms represent a wide range
of implementation approaches, and different hardware platforms have different
strengths. In this paper, we conduct comprehensive evaluations on three
representative big data systems: Intel Xeon, Atom (low power processors), and
many-core Tilera using BigDataBench - a big data benchmark suite. Then we
explore the relative performance of the three implementation approaches by
running BigDataBench, and provide strong guidance for the big data systems
construction. Through our experiments, we have inferred that a big data system
based on specific hardware has different performance in the context of
different applications and data volumes. When we construct a system, we should
take into account not only the performance or energy consumption of the pure
hardware, but also the characteristics of applications running on them. Data
scale, application type and complexity should be considered comprehensively
when researchers or architects plan to choose fundamental components for their
big data systems.
