  Recently, the SPARQL query language for RDF has reached the W3C
recommendation status. In response to this emerging standard, the database
community is currently exploring efficient storage techniques for RDF data and
evaluation strategies for SPARQL queries. A meaningful analysis and comparison
of these approaches necessitates a comprehensive and universal benchmark
platform. To this end, we have developed SP^2Bench, a publicly available,
language-specific SPARQL performance benchmark. SP^2Bench is settled in the
DBLP scenario and comprises both a data generator for creating arbitrarily
large DBLP-like documents and a set of carefully designed benchmark queries.
The generated documents mirror key characteristics and social-world
distributions encountered in the original DBLP data set, while the queries
implement meaningful requests on top of this data, covering a variety of SPARQL
operator constellations and RDF access patterns. As a proof of concept, we
apply SP^2Bench to existing engines and discuss their strengths and weaknesses
that follow immediately from the benchmark results.
