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
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