Data partitioning for semantic web

Semantic web database is an RDF database. Tremendous increase can be seen in semantic web data, as real life applications of semantic web are using this data. Efficient management of this data at a larger scale, and efficient query performance are the two major concerns. This work aims at analyzing query performance issues in terms of execution time and scalability using data partitioning techniques. An experiment is devised to show effect of data partitioning technique on query performance. It demonstrates the query performance analysis for partitioning techniques applied. Vertical partitioning, hybrid partitioning and property table was used to store the RDF data and query execution time is analyzed. The experiment was carried out on a very small dummy data and now it will be scaled up using Barton library catalogue