A Systematic Review of Cloud Computing, Big Data and Databases on the Cloud

Cloud computing has emerged as an initiative which offers great promise in improving access to computational resources that would otherwise be unattainable due to sheer cost. While some cloud computing concepts date back to the 1950s, it is recent new cloud architecture and platforms that shape the way that resources are leased using service-based models. However, some confusion exists regarding the relationship between cloud-based models and challenges in managing big data. Some attempt to solve the problem by replacing and upgrading physical infrastructures, while others look to intelligent software to improve the scalability of data analytics. What also remains unclear is the definition and positioning of cloud-orientated paradigms. This is important to establish as it gets to the heart of where the underlying challenges exist in terms of availability, virtualisation, partitioning and distribution, scalability and elasticity, and performance bottlenecks when managing data. The goal of this systematic review is to provide insight into the current state of cloud computing and big data research. We find that challenges have been gaining momentum in this area from 2008 to 2013. In this study, using a systematic review framework, 129 publications are evaluated. We conclude that the current cloud-computing based frameworks are potentially neglecting fundamental database properties regarding atomicity and durability issues.