Comparative Study Big Data SQL Frameworks

● The amount of data being generated on a daily basis is constantly increasing, pushing the limits of traditional data processing technologies. A consequence of this increase is the rise to new distributed Big Data engines. This book is focused on comparative study/benchmarking Big Data SQL frameworks, both open-source or proprietary.
● The Big Data SQL frameworks are compared with each other from three points of view: performance (total job execution time), feature availability and integration with other services. In order to provide an unbiased comparison, a similar underlying infrastructure was employed for each framework. More precisely, experiments were conducted on different Big Data SQL platforms hosted on two public cloud infrastructures: 1. Microsoft Azure 2. Google Cloud Platform
● The results obtained from conducting the experiments on both PaaS and SaaS platforms are meant to shed some light on the benefits that emerge when choosing one technology. Furthermore, based on these insights, existing Big Data engines could be further improved.

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