We describe the use of parallel execution techniques and measure the price of parallel execution in NonStop SQL/MP, a commercial parallel datahase system from Tandem Computers. Non-Stop SQL uses intra-operator parallelism to parallelize joins, groupings and scans. Parallel execution consists of starting up several processes and communicating data between them. Our measurements show (a) Startup costs are negligible when processes are reused rather than created afresh (b) Communication costs are significant -they may exceed the costs of operators such as scan, grouping or join. We also show two counter-examples to the common intuition that parallel execution reduces response time at the expense of increased work-parallel execution may reduce work or may increase response time depending on communication costs.All execution times reported in the paper are scaled. No inferences should be drawn about actual execution times. All query executions reported in the paper were created by bypassing the NonStop SQL optimizer. No inferences should be drawn about the behavior of the optimizer.