How to quickly build dashboards with time-series data

TimescaleDB continuous aggregates are a feature that allows users to speed up repetitive queries that aggregate over time, making it easier to analyze and visualize important real-time and historical metrics. This feature is particularly useful for building dashboards that require frequent updates with ad-hoc queries. TimescaleDB's automated partitioning and continuous aggregates reduce disk throughput and compute requirements when running historical aggregate queries, making it an ideal solution for organizations looking to expose their time-series data across teams. The feature supports out-of-order inserts, allows users to configure refresh intervals, lags, and maximum intervals per job, and provides statistics through `timescaledb_information.continuous_aggregate_stats`. By leveraging continuous aggregates, users can improve the performance of their dashboards and gain valuable insights from their time-series data.

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