In past years, geographical information systems have undergone spectacular development. Beside traditional applications, some new areas have been opened by the spread of navigation systems and the publication of geoinformation via Internet. These areas are in need of efficient data handling due to the changing spatial and descriptive data of objects. This article presents the AEGIS framework, which is a currently developed spatio-temporal data management system at the Author’s Institute. This framework will serve as the future platform of GIS education and research at Author’s Institute. It introduces a data model that aims to uniformly represent raster and vector data with temporal references, enables efficient data management using specialized indexing, and also supports internal revision control management of all editing operations.The framework intorduces an engine for data processing that automatically transforms operations for distributed execution using GPUs, allows fast operations even with large datasets and high scalability with regard to new methods. To demonstrate the usage of the system two case studies — segment-based image classification and agent-based traffic simulation — are also presented. Keywords: Geospatial Information Systems, spatio-temporal data, indexing data structures, parallel data processing, remotely sensed image classification, agent based traffic simulation.