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The aim of this paper is to analyze the efficiency of the QSQN method, which was proposed by us and Nguyen in [10] for evaluating queries to Horn knowledge bases. In order to compare QSQN with the well-known methods QSQR and the one based on the Magic-Set transformation, we have implemented all of these methods. We compare them using representative examples that appear in many articles on deductive databases. Our experimental results show that the QSQN method usually outperforms the two other methods. Apart from the experimental results, we also explain the reasons behind the good performance of QSQN.