Geographic Information Systems (GIS) are integral to various applications such as urban planning,environmental monitoring, and logistics, necessitating robust database management systems(DBMS) to handle complex spatial data. This thesis presents a comparative analysis of twoprominent DBMS: MongoDB and MySQL, evaluating their performance and suitability for GISapplications. The research includes a detailed examination of their differences in data managementand handling, performance metrics, and scalability. Through systematic benchmarks and rigoroustesting on query execution times, resource utilization, and spatial query accuracy, this studyhighlights the strengths and weaknesses of each database. MongoDB exhibited superiorperformance in write operations and flexibility for unstructured data, making it suitable for realtime data processing. In contrast, MySQL excelled in read operations and complex queryingcapabilities, ensuring robust data integrity for structured data environments. The findings of thisresearch provide valuable insights for GIS practitioners, guiding the optimal selection of a DBMSbased on specific application requirements, performance needs, and scalability considerations.