Compared to proteomics, computational platforms for glycoproteomics is at an early stage and many researchers rely on the manual interpretation of large data sets to gain structural insights into the glycoproteome. Over the last few years there has been a steady increase in the availability of bioinformatics tools for processing and annotating glycoproteomics data sets. This mini-review describes advances in the development of algorithms and software applications and their applications. Furthermore, an update on structural and analytical databases is presented with a focus on those resources still actively maintained by the community, and how these resources are now being integrated into glycoproteomics pipelines to improve data interpretation.