This systematic review investigates the structures of Destination Management Systems (DMS) in low-density regions. These regions are known for their unique cultural and natural assets but face challenges due to limited infrastructure and accessibility. With the tourism industry embracing digital transformation, DMS are becoming essential tools for leveraging these unique features to attract tourists. They help address challenges such as promoting lesser-known attractions and overcoming marketing limitations. The review emphasizes the significance of advanced technologies such as Big Data, IoT, AI, and machine learning in revolutionizing DMS. These technologies enable real-time data analysis and adaptive responses to the ever-changing tourism landscapes. By analyzing articles, conference papers, and case studies published between 2013 and 2024, the study explores the balance between scalability, trackability, agility, and maintainability in DMS architectures, which is crucial for destinations with limited resources. The review identifies various approaches to DMS design and implementation, demonstrating their effectiveness in different contexts. The results demonstrate the positive impact of these systems on the competitiveness and appeal of destinations by improving their visibility and accessibility. The analysis stresses the importance of continuous research on the technical aspects of implementing destination management systems and incorporating new technologies.