We examine two-sided markets where players arrive stochastically over time. The cost of matching a client and provider is heterogeneous, and the distribution of costs – but not their realization – is known. In this way, a social planner is faced with two contending objectives:(a) to reduce the players’ waiting time before getting matched; and (b) to reduce matching costs. In this paper, we aim to understand when and how these objectives are incompatible. We identify two regimes dependent on the ‘speed of improvement’ of the cost of matching with respect to market size. One regime results in a quick or cheap dilemma without ‘free lunch’: there exists no clearing schedule that is simultaneously optimal along both objectives. In that regime, we identify a unique breaking point signifying a stark reduction in matching cost contrasted by an increase in waiting time. The other regime features a window of opportunity in which free lunch can be achieved. Which scheduling policy is optimal depends on the heterogeneity of match costs. Under limited heterogeneity, e.g., when there is a finite number of possible match costs, greedy scheduling is approximately optimal, in line with the related literature. However, with more heterogeneity greedy scheduling is never optimal. Finally, we analyze a particular model where match costs are exponentially distributed and show that it is at the boundary of the no-free-lunch regime We then characterize the optimal clearing schedule for varying social planner desiderata