Big data benchmark suites must include a diversity of data and workloads to be useful in
fairly evaluating big data systems and architectures. However, using truly comprehensive …

As architecture, systems, and data management communities pay greater attention to
innovative big data systems and architecture, the pressure of benchmarking and evaluating …

In recent years, DRAM technology improvements have scaled at a much slower pace than
processors. While server processor core counts grow from 33% to 50% on a yearly cadence …

Recently, big data has been evolved into a buzzword from academia to industry all over the
world. Benchmarks are important tools for evaluating an IT system. However, benchmarking …

Big Data is characterized by the five V's-of Volume, Velocity, Variety, Veracity and Value.
Research on Big Data, that is, the practice of gaining insights from it, challenges the …

Big Data constitutes an opportunity for companies to empower their analysis. However, at
the moment there is no standard way for approaching Big Data projects. This, coupled with …

This article provides an overview of the challenges of big data, in the aspects of data scale,
data heterogeneity, data timeliness, and demand for deep analyzing, in correspondence …

Big Data computing platform has evolved to be a multi-tenant service. The service quality
matters because system failure or performance slowdown could adversely affect business …

Big data phenomenon refers to the practice of collection and processing of very large data
sets and associated systems and algorithms used to analyze these massive datasets …

As data continues to be produced in massive amounts, with increasing volume, velocity and
variety, big data projects are growing in frequency and importance. However, the growth in …