Storing data in RDF format helps in simpler data interchange among different researchers compared to present approaches. There has been tremendous increase in the applications that use RDF data. The nature of RDF data is such that it tends to increase explosively. This makes it necessary to consider the time for retrieval and scalability of data while selecting a suitable RDF data store for developing applications. The research concentrates on comparing BigOWLIM. Bigdata, 4store and Virtuoso RDF stores on basis of their scalability and performance of storing and retrieving cancer proteomics and mass spectrometry data using SPARQL queries. In this research the author compares RDF data stores on a single machine as baseline and extends 4store and BigOWLIM data stores on a cluster for comparison. The author uncovers that Virtuoso has the best performance on data consisting of less than 250,000 triples whereas 4store has better scalability and performance for the larger data.


RDF, Database, Semantic Web, Ontology, Data Stores

Date of this Version



Computer and Information Technology

Department Head

Jeffrey Brewer

Month of Graduation


Year of Graduation



Master of Science

Head of Graduate Program

Jeffrey Brewer

Advisor 1 or Chair of Committee

John Springer

Committee Member 1

John Springer

Committee Member 2

Kari Clase

Committee Member 3

Raymond Hansen