• DocumentCode
    243697
  • Title

    NoSQL Systems for Big Data Management

  • Author

    Gudivada, Venkat N. ; Rao, Dantam ; Raghavan, Vijay V.

  • Author_Institution
    Weisburg Div. of Comput. Sci., Marshall Univ., Huntington, WV, USA
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    190
  • Lastpage
    197
  • Abstract
    The advent of Big Data created a need for out-of-the-box horizontal scalability for data management systems. This ushered in an array of choices for Big Data management under the umbrella term NoSQL. In this paper, we provide a taxonomy and unified perspective on NoSQL systems. Using this perspective, we compare and contrast various NoSQL systems using multiple facets including system architecture, data model, query language, client API, scalability, and availability. We group current NoSQL systems into seven broad categories: Key-Value, Table-type/Column, Document, Graph, Native XML, Native Object, and Hybrid databases. We also describe application scenarios for each category to help the reader in choosing an appropriate NoSQL system for a given application. We conclude the paper by indicating future research directions.
  • Keywords
    Big Data; XML; application program interfaces; query languages; NoSQL systems; big data management; client API; data management systems; data model; hybrid databases; key-value; native XML; native object; out-of-the-box horizontal scalability; query language; system architecture; table-type-column; Availability; Big data; Data models; Database languages; Databases; Scalability; Servers; Big Data; Data Models; Document Databases; Graph Databases; Native XML Databases; NewSQL; NoSQL;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Services (SERVICES), 2014 IEEE World Congress on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5068-3
  • Type

    conf

  • DOI
    10.1109/SERVICES.2014.42
  • Filename
    6903264