Query generators producing sequences of SQL statements are embedded in many applications. As the execution time of such sequences is often far from optimal, their optimiza- tion is an important issue. Therefore, in (5) we proposed a rule-based optimization approach, which we called CGO (Coarse-Grained Optimization). Our first prototype used a heuristic, priority-based control strategy to choose the rewrite rules that should be applied to a given statement sequence. This worked well but there is still potential for im- provements. Thus, in (4) we have introduced an approach to provide cost estimates for statement sequences which is the basis for a cost-based CGO optimizer. It exploits histogram propagation and the optimizer of the underlying database system for this purpose. In this demonstration, we want to showcase the functionality and the effectiveness of our ap- proach. Thereto, we present a prototype of a cost-estimation component for statement sequences which implements this approach. It includes a graphical user interface to explain the histogram-propagation process and to report the results of the cost-estimation process. In the setup for this demon- stration, we use a TPC-H benchmark database with an ap- propriate set of sequences as sample scenario.