Technology mapping transforms a technology-independent representation into a technology-dependent one given a library of cells. This process is performed by means of local replacements that are extracted by matching sections of the subject graph to library cells. Matching techniques are classified mainly into pattern and Boolean. These two techniques differ in quality and number of generated matches, scalability, and run time. This paper proposes hybrid matching, a new methodology that integrates both techniques in a technology mapping algorithm. In particular, pattern matching is used to speed up the matching phase and support large cells. Boolean matching is used to increase the number of matches and quality. Compared to Boolean matching, we show that hybrid matching yields an average reduction in the area and run time by 6% and 25%, respectively, with similar delay.