Knowledge intensive applications rely on the usage of knowledge artifacts, called patterns, to represent in a compact and semantically rich way huge quantities of heterogeneous raw data. Due to pattern characteristics of patterns, specific systems are required for pattern management in order to model, store, retrieve and manipulate patterns in an efficient and effective way. Several theoretical and industrial approaches (relying on standard proposals, metadata management and business intelligence solutions) have already been proposed for pattern management. However, no critical comparison of the existing approaches has been proposed so far. The aim of this chapter is to provide such a comparison. In particular, specific issues concerning pattern management systems, pattern models and pattern languages are discussed. Several parameters are also identified that will be used in evaluating the effectiveness of theoretical and industrial proposals. The chapter is concluded with a discussion concerning additional issues in the context of pattern management.