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      • HARVEST
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      Comparison of Graph Databases and Relational Databases When Handling Large-Scale Social Data

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      CHEN-THESIS-2016.pdf (2.025Mb)
      Date
      2016-09-20
      Author
      Chen, Yaowen 1989-
      ORCID
      0000-0002-2328-5972
      Type
      Thesis
      Degree Level
      Masters
      Metadata
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      Abstract
      Over the past few years, with the rapid development of mobile technology, more people use mobile social applications, such as Facebook, Twitter and Weibo, in their daily lives, and there is an increasing amount of social data. Thus, finding a suitable storage approach to store and process the social data, especially for the large-scale social data, should be important for the social network companies. Traditionally, a relational database, which represents data in terms of tables, is widely used in the legacy applications. However, a graph database, which is a kind of NoSQL databases, is in a rapid development to handle the growing amount of unstructured or semi-structured data. The two kinds of storage approaches have their own advantages. For example, a relational database should be a more mature storage approach, and a graph database can handle graph-like data in an easier way. In this research, a comparison of capabilities for storing and processing large-scale social data between relational databases and graph databases is applied. Two kinds of analysis, the quantitative research analysis of storage cost and executing time and the qualitative analysis of five criteria, including maturity, ease of programming, flexibility, security and data visualization, are taken into the comparison to evaluate the performance of relational databases and graph databases when handling large-scale social data. Also, a simple mobile social application is developed for experiments. The comparison is used to figure out which kind of database is more suitable for handling large-scale social data, and it can compare more graph database models with real-world social data sets in the future research.
      Degree
      Master of Science (M.Sc.)
      Department
      Computer Science
      Program
      Computer Science
      Supervisor
      Deters, Ralph
      Committee
      McCalla, Gordon I.; Vassileva, Jenia; Dinh, Anh
      Copyright Date
      September 2016
      URI
      http://hdl.handle.net/10388/7434
      Subject
      Graph Databases
      Relational Database
      Benchmark
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