Storing and Indexing RDF Data in a Column-Oriented DBMS

Effcient RDF data management is an essential factor in realizing the Semantic Web vision. However, most existing RDF storage schemes based on row-store relational databases are constrained in terms of efficiency and scalability. In this paper, we propose an RDF storage scheme that implements sextuple indexing for RDF triples using a column-oriented DBMS. To evaluate the performance of our approach, large-scale datasets upto 13 million triples are generated and benchmark queries that cover important RDF join patterns are devised. The experimental results show that our approach outperforms the row-oriented DBMS approach by upto an order of magnitude and is even competitive to the best state-of-the-art native RDF store.