TimescaleDB 1.3 introduces automated continuous aggregates, which can massively speed up workloads that need to process large amounts of data by automatically maintaining the results from a query and allowing users to retrieve them as they would any other data. Continuous aggregates are created like regular views but do not perform the average when queried, unlike materialized views, and their refresh is automatic in the background as new data is added or old data is modified. This feature is unique to TimescaleDB, which tracks previous data updates and delays data points, ensuring that continuous aggregates can be recomputed on older data without slowing down INSERT operations. The system consists of a materialization hypertable, a query engine, an invalidation engine, and a materialization engine, all designed to ensure good performance. Continuous aggregates work with various built-in aggregate functions, including averages, counts, and sums, and users can define their own custom aggregation functions as long as they are parallel-safe.