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

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

Sikha Bagui, Loi Tang Nguyen
Copyright: © 2015 |Volume: 5 |Issue: 2 |Pages: 17
ISSN: 2156-1834|EISSN: 2156-1826|EISBN13: 9781466680043|DOI: 10.4018/IJCAC.2015040103
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MLA

Bagui, Sikha, and Loi Tang Nguyen. "Database Sharding: To Provide Fault Tolerance and Scalability of Big Data on the Cloud." IJCAC vol.5, no.2 2015: pp.36-52. http://doi.org/10.4018/IJCAC.2015040103

APA

Bagui, S. & Nguyen, L. T. (2015). Database Sharding: To Provide Fault Tolerance and Scalability of Big Data on the Cloud. International Journal of Cloud Applications and Computing (IJCAC), 5(2), 36-52. http://doi.org/10.4018/IJCAC.2015040103

Chicago

Bagui, Sikha, and Loi Tang Nguyen. "Database Sharding: To Provide Fault Tolerance and Scalability of Big Data on the Cloud," International Journal of Cloud Applications and Computing (IJCAC) 5, no.2: 36-52. http://doi.org/10.4018/IJCAC.2015040103

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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.

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