NoSQL Systems for Big Data Management

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 perspectiv...

Full description

Saved in:
Bibliographic Details
Main Authors: Gudivada, Venkat N., Rao, Dhana, Raghavan, Vijay V.
Format: Conference Proceeding
Language:English
Subjects:
Availability
Big data
Data models
Database languages
Document Databases
Graph Databases
Native XML Databases
NewSQL
NoSQL
Scalability
Servers
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2378-3818
DOI:10.1109/SERVICES.2014.42