Case memory maintenance in a Case-Based Reasoning system is important for two main reasons: (1) to control the case memory size; (2) to reduce irrelevant and redundant instances that may produce noise in the Case-Based Reasoning system. In this paper, we present two approaches to the maintenance of case memories. The foundation of both approaches are the Rough Sets Theory, but each one applies a different policy to delete or maintain the competence of the system and reduce, as much as possible, the size of the case memory. Experiments using different domains, most of them from the UCI repository, show that the reduction techniques maintain the comptence obtained by the original case memory. the results are compared with those obtained using well-known reduction techniques.