Abstract: Association rule mining is the one of the most important technique of the data mining. Its aim is to extract interesting correlations, frequent patterns and association among set of items in the transaction database. This paper presents a comparison between different association mining algorithms. All these algorithms are compared according to various factors like type of data set, support counting, rule generation, candidate generation and some other factor .The compared algorithms are presented together with some examples that lead to the final conclusions. Association rules are widely used in various areas such as telecommunication, market and risk management, inventory control etc.