In PostgreSQL, running aggregations over high data volumes can be challenging due to query latency. However, TimescaleDB offers a solution with continuous aggregates, which materialize aggregations ahead of time and provide an efficient mechanism to refresh materialized aggregates for up-to-date results. To set up and work with continuous aggregates, it is essential to create a refresh policy, manually materialize aggregates for any time bucket, aim to create a continuous aggregate with the WITH NO DATA option, choose your refresh policy wisely, save storage by dropping raw data while keeping materialized data, compress materialized data that you no longer need to refresh, and align your continuous aggregate time buckets to your time zone. Continuous aggregates come with limitations, such as requiring a time_bucket function and only querying one hypertable in the definition query. By following these best practices, developers can improve performance and speed when working with time-series data using TimescaleDB's continuous aggregates.