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dc.contributor.advisorKhan, Mumit
dc.contributor.authorSumaiya Binte Mostafa
dc.contributor.authorTabassum, Firoza
dc.date.accessioned2013-04-16T05:16:55Z
dc.date.available2013-04-16T05:16:55Z
dc.date.copyright2012
dc.date.issued12/12/2012
dc.identifier.otherID 08301001
dc.identifier.otherID 09101028
dc.identifier.urihttp://hdl.handle.net/10361/2303
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 93).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2012.en_US
dc.description.abstractA cloud database is a database that typically runs on a cloud computing platform. Of the databases available on the cloud, traditional data model is SQL-based. The recent trend is to move on to NOSQL data model. Now, the question is which database approach is better to choose in this era of ‘Big Data’? SQL databases are difficult to scale, meaning they are not natively suited to a cloud environment, although cloud database services based on SQL are attempting to address this challenge. On the other hand, NOSQL databases are built to service heavy read/write loads and are able scale up and down easily, and therefore they are more natively suited to running on the cloud. Our aim for thesis is to investigate suitable data storage for cloud. Considering the ‘Big Data’ scenario of today’s world, we set forth to choose the NOSQL database model as the preferred solution for cloud computing. This paper aims to show two investigations on different branches of cloud data storage. The first analysis is based on the case study of performance benchmarking on 3 popular NOSQL databases - MongoDB, Cassandra, and HBase. The next part of investigation includes an experiment on the most popular ‘Big Data’ management framework – namely, Hadoop. Hadoop uses MapReduce for parallel computation, but writing MapReduce function is hard for programmers. So, our experiment is to configure HIVE data warehousing system on the top of Hadoop as a wrapper, so that end users gets benefit of using a SQL-like language, which is known as ‘HiveQL’ and provided by HIVE even if with the environment of complex MapReduce function.en_US
dc.description.statementofresponsibilitySumaiya Binte Mostafa
dc.description.statementofresponsibilityFiroza Tabassum
dc.format.extent107 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectComputer science and engineering
dc.subjectCloud Dataen_US
dc.titleInvestigation cloud data storageen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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