Authors:
Bela Stantic
1
;
Juergen Bock
1
and
Irina Astrova
2
Affiliations:
1
Institute for Integrating and Intelligent Systems, Griffith University, Australia
;
2
Institute of Cybernetics, Tallinn University of Technology, Estonia
Keyword(s):
Resource Description Framework - RDF, RDF storage, Sematic Web.
Related
Ontology
Subjects/Areas/Topics:
Cloud Computing
;
Enterprise Information Systems
;
Semantic Web Technologies
;
Services Science
;
Software Agents and Internet Computing
Abstract:
The increasing popularity of the Semantic Web and Semantic Technologies require sophisticated ways to store huge amounts of semantic data. RDF together with the rule base RDF Schema have proved themselves as good candidates for storing semantic data due to the simplicity and high abstraction level. A number of large scale RDF data storage solutions have been proposed. Several typical representative have been discussed and compared in this work, namely Sesame, Kowari, YARS, Redland and Oracle’s RDF MATCH table function. We present a comparison of those approaches with respect to consideration of context information, supported access protocols, query languages, indexing methods, RDF Schema awareness, and implementation. We also identify applicability as well as discuss advantages and disadvantages of particular approach. Furthermore, an overview of storage requirements and performance tests has been presented. A summary of performance analysis and recommendations are given and discussed.