Abstract: A database system performs analytics on longitudinal data, such as medical histories with events occurring to patients over time. Input data is processed into streams of events. A set of indexes of event characteristics is generated. A set of patient event histories, partitioned by patient, is generated. Several copies of event data are stored, each copy being structured to support a specific analytical task. Data is partitioned and distributed over several hardware nodes to allow parallel queries. Definitions of sets of candidate patients are translated into sets of filters applied to the set of indexes. Data for these candidates are input to analytical modules. Reports from analysis are automatically generated to be compatible with standard guidelines for reporting. Workflows support one task or a set of closely related tasks by offering the user a defined sequence of query options and analytic choices specifically arranged for the task.