To cope with the increased complexity of systems, models are used to capture what
is considered the essence of a system. Such models are typically represented as a
graph, which is queried to gain insight into the modelled system. Often, the results
of these queries need to be adjusted according to updated requirements and are therefore
a subject of maintenance activities. It is thus necessary to support writing model
queries with adequate languages. However, in order to stay meaningful, the analysis
results need to be refreshed as soon as the underlying models change. Therefore, a
good execution speed is mandatory in order to cope with frequent model changes. In
this paper, we propose a benchmark to assess model query technologies in the presence
of model change sequences in the domain of social media. We present solutions to this
benchmark in a variety of 11 different tools and compare them with respect to explicitness
of incrementalization, asymptotic complexity and performance.
