Efficient Horizontal Scaling of Databases using Data Sharding Technique
Ragul R1, Arokia Paul Rajan R2
1Ragul R, MSc Student, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India.
2Dr Arokia Paul Rajan *, Associate Professor, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India.
Manuscript received on February 12, 2020. | Revised Manuscript received on February 22, 2020. | Manuscript published on March 10, 2020. | PP: 590-593 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2418039520/2020©BEIESP | DOI: 10.35940/ijitee.E2418.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: As the new era of computing technology begins with the start of the 21st century, the data produced by each person are increasing enormously day-by-day. Companies started to track one’s personal details from applications like media sharing, social networks, eCommerce, etc. since they have started to generate a lot of data traffic. The Database, where these heavy loads of generated data have been stored, had to scale out to handle the network traffic. Cloud computing arrival carves a solution for this trafficking problem by making data sharding a suitable option for scaling the data. This paper discusses about the importance of database sharding and the distribution of the database over the different server and also how sharding is helpful to scale the incoming amount of enormous data to control the data trafficking issues in the cloud database. Also compares the difference in the performance of database with and without sharding techniques using SQL server instance.
Keywords: Distributed Database, Scalability, Database Sharding, Horizontal Sharding
Scope of the Article: Software Engineering Techniques and Production Perspectives