Recentadvancementsinsensorandtrackingtechnologieshavefacilitatedthereal-timetrackingof marine vessels as they traverse the oceans. As a result, there is an increasing demand to analyze thesedatasets to derive insights into vessel movement patterns and to investigate activities occurring withinspecific spatial and temporal contexts. This survey offers a comprehensive review of contemporary researchin trajectory data mining, with a particular focus on maritime applications. The article collects and evaluatesstate-of-the-art algorithmic approaches and key techniques pertinent to various use case scenarios withinthis domain. Furthermore, this study provides an in-depth analysis of recent developments in trajectorydata mining as applied to the maritime sector, identifying available data sources and conducting a detailedexamination of significant applications, including trajectory forecasting, activity recognition, and trajectoryclustering.