OBJECTIVES:  Rare diseases research presents with many challenges. Real-world databases have been increasingly utilized in rare diseases, to understand diseases and evaluate treatment impacts. A review of published database studies in Fabry disease has been performed, to assess the landscape, utility and application of different types of databases in various regions and countries. METHODS:  A targeted literature review was conducted in PubMed and Embase for years 1980–2016, to identify studies utilizing data from various real-world databases, including medical, claims, pharmacy, hospital and other sources; registry studies were not included. RESULTS:  The search yielded a total of 42 studies conducted in various regions globally. The majority of the studies were published after 2007. A larger proportion was based on health care databases in Europe (n=33). Germany represented the country with the largest number of publications (n=9). Among the types of the data collection methods used, the majority were medical chart or EMR reviews (n=40). Most often these studies were done in specialized Fabry referral centers located in tertiary care hospitals. The majority were single center studies (n=27), while others were multi-center, and one of the studies was based on a home infusion database. The research questions evaluated ranged from understating disease manifestations and natural history, to assessing disease management and treatment impact. Many studies (62%) included long-term follow-up period, to understand natural history and/or long-term treatment outcomes. CONCLUSIONS:  During the last decade there has been an increasing use of real-world databases in rare diseases, including Fabry disease. The review of Fabry database studies showed the value of these approaches. Many studies included relatively large number of patients and long-term follow-ups, and richness of data that are otherwise hard and time consuming to achieve with other research approaches. Real-world databases offer an opportunity of providing needed data and answering research questions in rare diseases space.