Abstract
Analyzing large data is a challenging problem today, as there is an increasing trend of applications being expected to deal with vast amounts of data that usually do not fit in the main memory of a single machine. For such data-intensive applications, database research community has started to investigate cloud computing as a cost effective option to build scalable parallel data management systems which are capable of serving petabytes of data for millions of users. The goal of this panel is to initiate an open discussion within the community on data management challenges and opportunities in cloud computing. Potential topics to be discussed in the panel include: MapReduce framework, shared-nothing architecture, parallel query processing, security, analytical data management, transactional data management and fault tolerance.
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© 2012 Springer-Verlag Berlin Heidelberg
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Shim, K. et al. (2012). Data Management Challenges and Opportunities in Cloud Computing. In: Lee, Sg., Peng, Z., Zhou, X., Moon, YS., Unland, R., Yoo, J. (eds) Database Systems for Advanced Applications. DASFAA 2012. Lecture Notes in Computer Science, vol 7239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29035-0_30
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DOI: https://doi.org/10.1007/978-3-642-29035-0_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29034-3
Online ISBN: 978-3-642-29035-0
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