We describe the parallel, cluster-based implementation of an algorithm for the computation of a database operator known as the datacube. Though a number of efficient sequential algorithms have recently been proposed for this problem, very little research effort has been expended upon cost-effective parallelization techniques. Our approach builds directly upon the existing sequential proposals and is designed to be both load balanced and communication efficient. We also provide experimental results that demonstrate the viability of our technique under a variety of test conditions. Ultimately, we show that parallel performance relative to the underlying sequential algorithm (speedup) is near optimal.