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Efficient querying of huge volumes of multidimensional data stored in cloud computing systems has become a necessity, due to the widespread of cloud storage facilities. With clouds getting larger and available data growing larger and larger it is mandatory to develop fast, scalable and efficient indexing schemes. In this paper, we propose the A-tree, a distributed indexing scheme for multidimensional data capable of handling both point and range queries, appropriate for cloud computing environments. A performance evaluation of the A-tree against the state-of-the-art competitor attests its superiority, achieving significantly lower latencies.