The Electron Microscopy DataBank (EMDB) is growing rapidly, accumulating biological structural data obtained cryo-electron microscopy (cryo-EM). Cryo-EM is an emerging technique for determining large biomolecular complexes and subcellular structures. Together with the Protein Data Bank (PDB), EMDB is becoming a fundamental resource of the tertiary structures of biological macromolecules. To take full advantage of this indispensable resource, the ability to search the database by structural similarity is essential. However, unlike high-resolution structures stored in PDB, methods for comparing low-resolution EM density maps are not well established. Here, we developed a novel computational method for efficiently searching EM maps. The method uses a compact fingerprint representation of EM maps based on the 3D Zernike descriptor, which is a mathematical series expansion for representing isosurface shape of EM maps. The method was implemented in a web server, named EM-SURFER (http://kiharalab.org/em-surfer/), which allows users to search against the entire EMDB with over 2400 entries in a few seconds. By combing with map segmentation, the method can also identify corresponding local regions in EM maps. Examples of search results from different types of query structures are discussed. The unique capability of EM-SURFER to detect 3D shape similarity of low-resolution EM maps should prove invaluable in structural biology.