Efficient Processing of Semantic Web Queries in HBase and MySQL Cluster

Author

Franke, C. ; Morin, Sonia ; Chebotko, Artem ; Abraham, Jibi ; Brazier, Pearl

Volume

15

Issue

3

fYear

2013

fDate

May-June 2013

Firstpage

36

Lastpage

43

Abstract

With rapid growth of the Semantic Web, the authors´ research focuses on designing a scalable resource description framework (RDF) database system that can efficiently process SPARQL queries over large RDF datasets. In this article, they present their design, architecture, storage schemes, and performance evaluation of two efficient RDF data management approaches that use state-of-the-art cloud and relational database technologies-HBase and MySQL Cluster.

Keywords

SQL; cloud computing; pattern clustering; relational databases; semantic Web; HBase cluster; MySQL cluster; cloud technology; data management approach; relational database; resource description framework; scalable RDF database system; semantic Web query; Clustering algorithms; Databases; Distributed processing; Information technology; Middleware; Performance evaluation; Query processing; Resource description framework; Semantic Web; HBase; MySQL Cluster; RDF; SPARQL; SQL; Semantic Web; cloud computing; distributed database; information technology; query; performance; scalability;

fLanguage

English

Journal_Title

IT Professional

Publisher

ieee

ISSN

1520-9202

Type

jour

DOI

10.1109/MITP.2012.42

Filename

6174994