To speed up queries by aggregating your data, consider using PostgreSQL's materialized views or TimescaleDB's continuous aggregates. Materialized views can provide faster query performance but require manual refreshes after data updates, which can be time-consuming and may lead to outdated data. In contrast, continuous aggregates automatically update with new data, providing more flexibility and reducing the need for manual refreshes. However, they also come with limitations, such as requiring a `time_bucket` function and limiting query capabilities. To get the best performance from continuous aggregates, create a refresh policy that matches your use case, schedule it to run frequently enough to keep up with data changes, and consider compressing aggregated data older than your refresh policy's window_start parameter value. Additionally, align your time bucket to your time zone and remember that manual materialization of aggregates for any time bucket can be done using the `refresh_continuous_aggregate` function. By following these best practices, you can improve performance and speed when working with PostgreSQL data aggregation.