The next decade promises to be an exciting time for astronomers. Large volumes of astronomical data are continuously collected from highly productive space missions. This data has to be efficiently stored and analyzed in such a way that astronomers maximize their scientific return from these missions. Recognizing the need to better handle astronomical datasets, we designed ASTROIDE, adistributed data server for astronomical data. We analyze the peculiarities of the data and the queries in cosmological applications and design a new framework where astronomers can explore and manage vast amounts of data. ASTROIDE introduces effective methods for efficient astronomical query execution on Spark through data partitioning with HEALPix and customized optimizer. ASTROIDE offers a simple, expressive and unified interface through ADQL, a standard language for querying databases in astronomy. Experiments have shown that ASTROIDE is effective in processing astronomical data, scalable and outperforms the state-of-the-art.