A “Query Optimizer” provides a cost estimation metric referred to as “Maximum Accumulated Overload” (MAO). MAO is approximately equivalent to maximum system latency in a data stream management system (DSMS). Consequently, MAO is directly relevant for use in optimizing latencies in real-time streaming applications running multiple continuous queries (CQs) over high data-rate event sources. In various embodiments, the Query Optimizer computes MAO given knowledge of original operator statistics, including “operator selectivity” and “cycles / event” in combination with an expected event arrival workload. Beyond use in query optimization to minimize worst-case latency, MAO is useful for addressing problems including admission control, system provisioning, user latency reporting, operator placements (in a multi-node environment), etc. In addition, MAO, as a surrogate for worst-case latency, is generally applicable beyond streaming systems, to any queue-based workflow system with control over the scheduling strategy.