One of the most challenging problems in the migration of a monolith to a microservices architecture is the identification of the microservices boundaries. Several approaches have been recently proposed for the automatic identification of microservices, which, even though following the same basic steps, diverge on how data of the monolith system is collected and analysed. In this paper, we compare the decompositions generated for two monolith systems into a set of candidate microservices, when static and dynamic analysis data collection techniques are used. The decompositions are generated using a combination of similarity measures and are evaluated according to a complexity metric to answer the following research question: which collection of monolith data, static or dynamic analysis, allows to generate better decompositions? As result of the analysis we conclude that neither of the analysis techniques, static nor dynamic, outperforms the other, but the dynamic collection of data requires more effort.