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Database systems have long optimized for parallel execution; the research community has pursued parallel database machines since the early `80s, and several the key ideas from that era underlie the design and success of commercial database engines today. Computer architectures have shifted drastically during the intervening decades, however, and today the constraints of semiconductor technology combine with Moore's Law to double the number of processors per chip every 18 months. Converting this available raw parallelism into scalable performance is increasingly difficult with conventional servers, for both business intelligence and transaction processing workloads.