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Database Sharding: To Provide Fault Tolerance and Scalability of Big Data on the Cloud

Author

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  • Sikha Bagui

    (Department of Computer Science, University of West Florida, Pensacola, FL, USA)

  • Loi Tang Nguyen

    (Naval Education and Training, Development and Technology Center (NETPDTC), Pensacola, FL, USA)

Abstract

In this paper, the authors present an architecture and implementation of a distributed database system using sharding to provide high availability, fault-tolerance, and scalability of large databases in the cloud. Sharding, or horizontal partitioning, is used to disperse the data among the data nodes located on commodity servers for effective management of big data on the cloud.

Suggested Citation

  • Sikha Bagui & Loi Tang Nguyen, 2015. "Database Sharding: To Provide Fault Tolerance and Scalability of Big Data on the Cloud," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 5(2), pages 36-52, April.
    • Handle: RePEc:igg:jcac00:v:5:y:2015:i:2:p:36-52
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    Cited by:

    1. Stanisavljević, Vladimir, 2019. "Utilizing Edge Computing for Monitoring Plant Productivity in Print Industry," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2019), Rovinj, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019, pages 92-99, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.

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