Data Deduplication Techniques for Big Data Storage Systems
Niteesha Sharma1, A. V. Krishna Prasad2, V. Kakulapati3
1Niteesha Sharma, IT Department, Anurag Group of Institutions, Ghatkesar, India.
2Dr. A. V. Krishna Prasad, CSE Department, MVSR Engineering College, Hyderabad, India.
3Dr. V. Kakulapati, IT Department, Sreenidhi Institute of Science and Technology, Ghatkesar, India.
Manuscript received on 04 July 2019 | Revised Manuscript received on 08 July 2019 | Manuscript published on 30 August 2019 | PP: 1145-1150 | Volume-8 Issue-10, August 2019 | Retrieval Number: J91290881019/2019©BEIESP | DOI: 10.35940/ijitee.J9129.0881019
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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: The enormous growth of digital data, especially the data in unstructured format has brought a tremendous challenge on data analysis as well as the data storage systems which are essentially increasing the cost and performance of the backup systems. The traditional systems do not provide any optimization techniques to keep the duplicated data from being backed up. Deduplication of data has become an essential and financial way of the capacity optimization technique which replaces the redundant data. The following paper reviews the deduplication process, types of deduplication and techniques available for data deduplication. Also, many approaches proposed by various researchers on deduplication in Big data storage systems are studied and compared.
Keywords: Big data, storage, deduplication, redundancy, process.
Scope of the Article: Big Data Analytics