A couple years ago it occured to me that a database with column-oriented storage, such as Sybase IQ, might make a reasonable database for storing RDF data, where a star schema can be seen as a way to represent related tuples together.
Now it turns out some folks have been working on such a thing... C-Store is an open source, column-oriented databse. The paper "Scalable Semantic Web Data Management Using Vertical Partitioning" (pdf) discusses using C-Store for RDF...
Efficient management of RDF data is an important factor in realizing the Semantic Web vision. Performance and scalability issues are becoming increasingly pressing as Semantic Web technology is applied to real-world applications. In this paper, we examine the reasons why current data management solutions for RDF data scale poorly, and explore the fundamental scalability limitations of these approaches. We review the state of the art for improving performance for RDF databases and consider a recent suggestion, “property tables.” We then discuss practically and empirically why this solution has undesirable features. As an improvement, we propose an alternative solution: vertically partitioning the RDF data. We compare the performance of vertical partitioning with prior art on queries generated by a Web-based RDF browser over a large-scale (more than 50 million triples) catalog of library data. Our results show that a vertical partitioned schema achieves similar performance to the property table technique while being much simpler to design. Further, if a column-oriented DBMS (a database architected specially for the vertically partitioned case) is used instead of a row-oriented DBMS, another order of magnitude performance improvement is observed, with query times dropping from minutes to several seconds.
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C-Store is the starting code base for Vertica. C-Store was started at MIT by Dr. Stonebraker, as a student project I believe, and Vertica is his VC backed startup to commercialize the ideas.
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