For clustering, DBSCAN surpass k-means in terms of handling arbitrary  shape data sets. In the most published papers about density based clustering, the experiments are performed with synthetic data sets that have special features (for example, the moon-shaped data sets). Can someone point me to some real world datasets where DBSCAN outperforms K-means. 
For which real world data sets does DBSCAN surpass K-means.?
machine learning;clustering;dataset;k means;clusters