Commercial OLAP systems usually treat OLAP dimensions as static entities. In practice, dimension updates are often necessary in order to adapt the multidimensional database to changing requirements. In earlier work we proposed a temporal multidimensional model and TOLAP, a query language supporting it, accounting for dimension updates and schema evolution at a high level of abstraction. In this paper we present our implementation of the model and the query language. We show how to translate a TOLAP program to SQL, and present a real-life case study, a medical center in Buenos Aires. We apply our implementation to this case study in order to show how our approach can address problems that occur in real situations and that current non-temporal commercial systems cannot deal with. We present results on query and dimension update performance, and briefly describe a visualization tool that allows editing and running TOLAP queries, performing dimension updates, and browsing dimensions across time.