The recent advances in database technology have enabled the development of a new generation of spatial databases, where the DBMS is able to manage spatial and non-spatial data types together. Most spatial databases can deal with vector geometries (e.g., polygons, lines and points), but have limited facilities for handling image data. However, the widespread availability of high-resolution remote sensing images has improved considerably the application of images to environmental monitoring and urban management. Therefore, it is increasingly important to build databases capable of dealing with images together with other spatial and non-spatial data types. With this motivation, this paper describes a solution for efficient handling of large image data sets in a standard object-relational database management system. By means of adequate indexing, compression and retrieval techniques, satisfactory performances can be achieved using a standard DBMS, even for very large satellite images. Thi...