NoSQL Systems for Big Data Management

被引：44

作者：

Gudivada, Venkat N. ^{[1
]}

Rao, Dhana ^{[2
]}

Raghavan, Vijay V. ^{[3
]}

机构：

[1] Marshall Univ, Weisburg Div Comp Sci, Huntington, WV 25755 USA

[2] Marshall Univ, Dept Biol Sci, Huntington, WV USA

[3] Univ Louisiana Lafayette, Ctr Adv Comp Studies, Lafayette, LA 70504 USA

来源：

2014 IEEE WORLD CONGRESS ON SERVICES (SERVICES) | 2014年

关键词：

Data Models; NoSQL; NewSQL; Big Data; Graph Databases; Document Databases; Native XML Databases;

D O I：

10.1109/SERVICES.2014.42

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：190 / 197

页数：8

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