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
fDate :
June 27 2014-July 2 2014
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;
Conference_Titel :
Services (SERVICES), 2014 IEEE World Congress on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4799-5068-3
DOI :
10.1109/SERVICES.2014.42
