Partitioning of temporal databases can implement distributed storage of temporal data via time-based or space-based techniques to improve performance of operators on the database. A variety of operators can be supported for the partitioned tables, including temporal aggregation, time travel, and temporal join. The use of checkpoints can greatly increase performance in a variety of scenarios. The described partitioning techniques can be applied in a parallel execution context to great benefit. The partitioning can also reduce local memory footprint, facilitating in-memory database processing.