Over the years, many schema matching approaches have been developed to discover correspondences between schemas. Although this task is crucial in data integration, its evaluation, both in terms of matching quality and time performance, is still manually performed. Indeed, there is no common platform which gathers a collection of schema matching datasets to fulfil this goal. Another problem deals with the measuring of the post-match effort, a human cost that schema matching approaches aim at reducing. Consequently, we propose XBenchMatch, a schema matching benchmark with available datasets and new measures to evaluate this manual post-match effort and the quality of integrated schemas. We finally report the results obtained by different approaches, namely COMA++, Similarity Flooding and YAM. We show that such a benchmark is required to understand the advantages and failures of schema matching approaches. Therefore, it could help an end-user to select a schema matching tool which covers his/her needs.