Concepts, comparisons, architecture, how features connect, and the glossary
Architectural choices and optimizations that power TimescaleDB and Tiger Cloud for real-time analytics
Tiger CloudManaged service basics, supported regions, and features only available in the cloud
Capabilities & comparisonHow TimescaleDB capabilities fit together and how Tiger Cloud and self-hosted options compare
Table layout: wide, narrow, or mediumHow table shape affects metrics, schema changes, and queries before you commit to a hypertable
Data model: keys and time columnsPartition columns, primary keys, and unique constraints for hypertables, before you load data
Hypertables & chunksTime partitioning, chunk intervals, and how data is organized at scale
HypercoreColumnar storage, compression, and how hypercore relates to hypertables and chunks
Continuous aggregates (CAGGs)How continuous aggregates work, real-time aggregates and hierarchical aggregates, materialized hypertables, and timezone handling
Data lifecycleRetention, tiered storage, and Tiger Cloud policies for dropping old data and moving colder data
Deep diveHub for advanced topics and longer-form architecture material beyond the whitepaper
GlossaryDefinitions for engineering, database, and product terms used throughout the docs
For quickstarts, examples, and how-tos, see Build.
