Because of the massive growth of the spatial data on the cloud, the efficiency of retrieving algorithms of such data is a necessity. In this paper, we evaluate the efficiency for huge datasets spatial indexing and retrieving at cloud computing environment. One of the most common data structures is selected for this study namely the priority R-tree (PR-Tree). The priority R-tree for spatial indexing as it is an optimal variation of the R-tree and more efficient for extreme datasets. First, we implemented the priority R-tree then we deployed it on various cloud instances. Second, we evaluated the performance of running this application. Finally, we recorded the results which can be helpful in case of retrieving huge datasets on the cloud