Abstract

Scalable database management systems (DBMS)—both for update intensive application workloads as well as decision support systems for descriptive and deep analytics—are a critical part of the cloud infrastructure and play an important role in ensuring the smooth transition of applications from the traditional enterprise infrastructures to next generation cloud infrastructures. Though scalable data management has been a vision for more than three decades and much research has focussed on large scale data management in traditional enterprise setting, cloud computing brings its own set of novel challenges that must be addressed to ensure the success of data management solutions in the cloud environment. This paper presents an organized picture of the challenges faced by application developers and DBMS designers in developing and deploying internet scale applications. Our background study encompasses both classes of systems: (i) for supporting update heavy applications, and (it) for ad-hoc analytics and decision support. We then focus on providing an in-depth analysis of systems for supporting update intensive web-applications and provide a survey of the state-of-the-art in this domain. We crystallize the design choices made by some successful systems large scale database management systems, analyze the application Demands and access patterns, and enumerate the desiderata for a cloud-bound DBMS.

Keywords: Database management systems, Cloud infrastructure and decision support.

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 How to Cite
[1]
Kokila, P.M., Saravanan, P., Jagadeesan, D.B. and Sharmila, R. 2016. Views of Current and Future Opportunities of Big Data. International Journal of Science and Engineering Invention. (Sep. 2016), 187 to 191. DOI:https://doi.org/10.23958/ijsei/vol02-i07/02.

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