Retrieval of information from the databases is now-a-day's significant issues. The thrust of information for decision making is challenging one. To overcome this problem, different techniques have been developed for this purpose. One of techniques is clustering. Clustering is a significant task in data analysis and data mining applications. It is the task of arrangement a set of objects so that objects in the identical group are more related to each other than to those in other groups (clusters).The clustering is unsupervised learning. In this paper, the authors propose a methodology for comparing clustering methods based on the quality of the result and the performance of the execution.