Big Data in Cloud Environment

Authors

  • Poornima Sharma SS, RGPV University, Bhopal
  • Varun Garg SS, RGPV University, Bhopal, India
  • Randeep Kaur CSE,GGITS Jabalpur, RGPV University, Bhopal, India
  • Satendra Sonare CSE,GGITS Jabalpur, RGPV University, Bhopal, India

Keywords:

Big Data, Cloud computing, Map/Reduce

Abstract

Big Data concerns large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data is now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. However, big data entails a huge commitment of hardware and processing resources, making adoption costs of big data technology prohibitive to small and medium sized businesses. Cloud computing offers the promise of big data implementation to small and medium sized businesses. Big Data processing is performed through a programming paradigm known as MapReduce. Typically, implementation of the MapReduce paradigm requires networked attached storage and parallel processing. The computing needs of MapReduce programming are often beyond what small and medium sized business are able to commit. Cloud computing is on-demand network access to computing resources, provided by an outside entity. Common deployment models for cloud computing include platform as a service (PaaS), software as a service (SaaS), infrastructure as a service (IaaS) & hardware as a service (HaaS).

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Published

2013-11-30

How to Cite

[1]
P. Sharma, V. Garg, R. Kaur, and S. Sonare, “Big Data in Cloud Environment”, Int. J. Comp. Sci. Eng., vol. 1, no. 3, pp. 15–17, Nov. 2013.

Issue

Vol. 1 No. 3 (2013): IJCSE November Edition

Section

Review Article

License

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