Many viruses are capable of integrating in the human genome, particularly viruses involved in tumorigenesis. Viral integrations can be considered genetic markers for discovering virus-caused cancers and inferring cancer cell development. Next-generation sequencing (NGS) technologies have been widely used to screen for viral integrations in cancer genomes, and a number of bioinformatics tools have been developed to detect viral integrations using NGS data. However, there has been no systematic comparison of the methods or software. In this study, we performed a comprehensive comparative analysis of the designs, performance, functionality and limitations among the existing methods and software for detecting viral integrations. We further compared the sensitivity, precision and runtime of integration detection of four representative tools. Our analyses showed that each of the existing software had its own merits, however, none of them were sufficient for parallel or accurate virome-wide detection. After carefully evaluating the limitations shared by the existing methods, we proposed strategies and directions for developing virome-wide integration detection.