  Analytical queries over RDF data are becoming prominent as a result of the
proliferation of knowledge graphs. Yet, RDF databases are not optimized to
perform such queries efficiently, leading to long processing times. A well
known technique to improve the performance of analytical queries is to exploit
materialized views. Although popular in relational databases, view
materialization for RDF and SPARQL has not yet transitioned into practice, due
to the non-trivial application to the RDF graph model. Motivated by a lack of
understanding of the impact of view materialization alternatives for RDF data,
we demonstrate SOFOS, a system that implements and compares several cost models
for view materialization. SOFOS is, to the best of our knowledge, the first
attempt to adapt cost models, initially studied in relational data, to the
generic RDF setting, and to propose new ones, analyzing their pitfalls and
merits. SOFOS takes an RDF dataset and an analytical query for some facet in
the data, and compares and evaluates alternative cost models, displaying
statistics and insights about time, memory consumption, and query
characteristics.
