Mining frequent structural patterns from graph databases is an important research problem with broad applications. Recently, we developed an e?ective index structure, ADI, and e±cient algorithms for mining frequent patterns from large, disk-based graph databases [5], as well as constraint-based mining techniques. The techniques have been integrated into a research prototype system|GraphMiner. In this paper, we describe a demo of GraphMiner which showcases the technical details of the index structure and the mining algorithms including their e±cient implementation, the mining performance and the comparison with some state-of-the-art methods, the constraint-based graph-pattern mining techniques and the procedure of constrained graph mining, as well as mining real data sets in novel applications.