This story was originally published on HackerNoon at:
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Learn why late-arriving time-series data can leave aggregates stale and how TimescaleDB continuous aggregate refresh windows determine reconciling corrections.
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Late-arriving and corrected time-series data can make pre-computed dashboards report plausible but stale numbers. This article compares four aggregation strategies, from scheduled materialized views and insert-triggered views to streaming dataflows and TimescaleDB continuous aggregates. It explains how invalidation tracking works and why the start_offset and end_offset of a refresh policy determine whether late data is ever reconciled.