The performance of transactional database systems is typically evaluated by measuring the amount of transactions they can commit to the database per second. However, fairly measuring this for the same workload on different systems is not trivial. It is therefore relevant to formalize schedule efficiency, investigate the space of all possible efficient schedules, and identify whether there is any room for improvement. Prior transaction theory largely centers on decision problems relating to safety, such as the serializability, robustness, and allocation problems. Most pertinently, these problems take already scheduled transactions as input, and do not directly consider the efficiency of those schedules. In this work, we define schedules as assignments of operations on objects to discrete points in time. This allows us to quantify efficiency as the elapsed duration between the schedule’s beginning and end, more commonly known as the makespan in the scheduling literature. We establish that, given some set of transactions and a desired makespan, it is NP-complete to decide if there exists a conflict serializable schedule which is bounded by that makespan. We additionally provide an instance optimal algorithm for scheduling transaction sets with a single contention point, that is, exactly one object may appear in conflicting operations. Lastly, we give worst-case optimal bounds on the makespan, meaning that schedules can never exceed this bound, and for the worst transaction sets, the bound is optimal.