J Grid Computing DOI 10.1007/s10723-016-9371-1 Big Data 2.0 Processing Systems: Taxonomy and Open Challenges Fuad Bajaber · Radwa Elshawi · Omar Batarfi · Abdulrahman Altalhi · Ahmed Barnawi · Sherif Sakr Received: 16 July 2015 / Accepted: 14 June 2016 © Springer Science+Business Media Dordrecht 2016 Abstract Data is key resource in the modern world. Big data has become a popular term which is used to describe the exponential growth and availability of data. In practice, the growing demand for large-scale data processing and data analysis applications spurred the development of novel solutions from both the industry and academia. For a decade, the MapReduce framework, and its open source realization, Hadoop, has emerged as a highly successful framework that has F. Bajaber · O. Batarfi · A. Altalhi · A. Barnawi King Abdulaziz University, Jeddah, Saudi Arabia F. Bajaber e-mail: fbajaber@kau.edu.sa O. Batarfi e-mail: obatarfi@kau.edu.sa A. Altalhi e-mail: ahaltalhi@kau.edu.sa A. Barnawi e-mail: ambarnawi@kau.edu.sa R. Elshawi Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia e-mail: rmelshawi@pnu.edu.sa S. Sakr () University of New South Wales, Sydney, NSW, Australia e-mail: ssakr@cse.unsw.edu.au S. Sakr King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia created a lot of momentum in both the research and industrial communities such that it has become the defacto standard of big data processing platforms. However, in recent years, academia and industry have started to recognize the limitations of the Hadoop framework in several application domains and big data processing scenarios such as large scale processing of structured data, graph data and streaming data. Thus, we have witnessed an unprecedented interest to tackle these challenges with new solutions which constituted a new wave of mostly domain-specific, optimized big data processing platforms. In this article, we refer to this new wave of systems as Big Data 2.0 processing systems. To better understand the latest ongoing devel- opments in the world of big data processing systems, we provide a taxonomy and detailed analysis of the state-of-the-art in this domain. In addition, we iden- tify a set of the current open research challenges and discuss some promising directions for future research. Keywords Big data · Hadoop 1 Introduction The radical expansion and integration of computation, networking, digital devices and data storage has pro- vided a robust platform for the explosion in big data as well as being the means by which big data are gen- erated, processed, shared and analyzed. In the field of computer science, data is considered as the main raw