📄️ Continuous Aggregates
Continuous aggregates in TimescaleDB are materialized views designed specifically for time-series data. They automatically maintain pre-computed aggregations of data from a source hypertable, dramatically improving query performance for analytical workloads. Unlike standard materialized views, continuous aggregates refresh incrementally, only processing new data since the last refresh rather than recalculating the entire aggregate.
📄️ Hypertables
Hypertables are the core feature of TimescaleDB, automatically partitioning your data by time and other dimensions into smaller, more manageable child tables called "chunks." This architecture is the key to achieving fast ingest rates and query performance on large time-series datasets.
📄️ Reorder Policies
A reorder policy reorganizes data in a hypertable's chunks to match the order of a specific index. This process can significantly improve query performance, especially for queries that read data in the index's order, as it reduces the number of disk pages that need to be read.
📄️ Retention Policies
A retention policy automatically drops old chunks from a hypertable or continuous aggregate on a scheduled basis. This keeps storage consumption bounded without requiring manual intervention and is the standard approach for managing time-series data lifecycle in TimescaleDB.