The document discusses developing an open benchmarking framework called LITMUS to evaluate diverse data management systems (DMSs) in a standardized way. It addresses key challenges in 1) converting between data models like RDF and property graphs, 2) translating queries between languages like SPARQL and Gremlin, and 3) selecting appropriate key performance indicators (KPIs). LITMUS is designed with modules for data integration, querying, profiling system performance, and analyzing results. Addressing the challenges of data conversion, query translation, and metrics selection is needed to realize LITMUS' goal of enabling automated, cross-domain benchmarking of different types of DMSs.