Abstract
The development and extensive use of highly distributed and scalable systems to process Big Data is widely considered. New data management architectures, e.g. distributed file systems and NoSQL databases, are used in this context. On the other hand, features of Big Data like their complexity and data analytics demands indicate that these tools solve Big Data problems only partially. A development of so called NewSQL databases is highly relevant and even special category of Big Data Management Systems is considered. In this work we will shortly discuss these trends and evaluate some current approaches to Big Data management and processing, identify the current challenges, and suggest possible research directions.
Chapter PDF
Similar content being viewed by others
References
Baeza-Yates, R.: Big Data or Right Data? In: Proc. of the 7th Alberto Mendelzon Int. Workshop on Foundations of Data Management, Puebla/Cholula, Mexico, May 21-23. CEUR-WS.org (2013)
Behm, A., Borkar, V.R., Carey, R.M., Grover, J., et al.: ASTERIX: Towards a Scalable, Semistructured Data Platform for Evolving-world Models. Distributed and Parallel Databases 29(3), 185–216 (2011)
Bu, Y., Howe, Y., Balazinska, M., Ernstm, M.D.: The HaLoop approach to large-scale iterative data analysis. The VLDB Journal 21(2), 169–190 (2012)
Corbett, J.C., Dean, J.C., Epstein, M., et al.: Spanner: Google’s Globally-Distributed Database. In: Proc. of 10th USENIX Symposium on Operation Systems Design and Implementation (OSDI 2012), pp. 261–264 (2012)
Dean, D., Ghemawat, S.: MapReduce: Simplified Data Processing on Large Clus-ters. Communications the ACM 51(1), 107–113 (2008)
Hecht, R., Jablonski, S.: NoSQL evaluation: A use case oriented survey. In: CSC 2011 Proceedings of the 2011 International Conference on Cloud and Service Computing, pp. 336–341 (2011)
Kelly, J.: Big Data: Hadoop, Business Analytics and Beyond, Wikibon (2014), http://wikibon.org/wiki/v/Big_Data:_Hadoop,_Business_Analytics_and_Beyond (accessed July 20, 2014)
Leskovec, J., Rajaman, A., Ullman, J.D.: Mining of Massive Datasets. Cambridge University Press, Cambridge (2011)
Pokorny, J.: NoSQL Databases: a step to databases scalability in Web environ-ment. International Journal of Web Information Systems 9(1), 69–82 (2013)
Shute, J., Vingralek, R., Samwel, B., et al.: F1: A Distributed SQL Database That Scales. PVLDB 6(11), 1068–1079 (2013)
Shvachko, K., Kuang, H., Radia, S., Chansler, R.: The Hadoop Distributed File System. In: Proceedings of MSST2010, pp. 1–10. IEEE Press (2010)
Stuart, J., Barker, A.: Undefined By Data: A Survey of Big Data Definitions. CoRR, arXiv:1309.5821 (2013)
Vinayak, R., Borkar, V., Carey, M.-J., Li, C.: Big data platforms: what’s next? ACM Cross Road 1, 44–49 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 IFIP International Federation for Information Processing
About this paper
Cite this paper
Pokorný, J. (2014). How to Store and Process Big Data: Are Today’s Databases Sufficient?. In: Saeed, K., Snášel, V. (eds) Computer Information Systems and Industrial Management. CISIM 2015. Lecture Notes in Computer Science, vol 8838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45237-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-662-45237-0_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45236-3
Online ISBN: 978-3-662-45237-0
eBook Packages: Computer ScienceComputer Science (R0)