Data tiering overview

Time-series data accumulates rapidly and the value of older data typically decreases over time. To control storage costs without losing access to historical data, you can move older chunks from local storage to lower-cost object storage while keeping them fully queryable through the same hypertable.

With Tiger Cloud, you can manually tier individual chunks or implement automated policies using these APIs.

For more information about working with tiered data, see Manage storage and tiering.

Samples

Create a tiering policy to move chunks older than 3 weeks to object storage

SELECT add_tiering_policy('assets_candlestick_daily', INTERVAL '3 weeks');

When you call add_tiering_policy, chunks fully older than the supplied interval are frozen and queued for upload to object storage in the background.

Create a tiering policy with an integer-based time column

SELECT add_tiering_policy('events', BIGINT '1000000');

Manually tier an individual chunk

SELECT tier_chunk('_timescaledb_internal._hyper_1_1_chunk');

Bring a tiered chunk back into local storage

CALL untier_chunk('_hyper_1_1_chunk');

Remove a tiering policy

SELECT remove_tiering_policy('assets_candlestick_daily');

Removes the existing tiering policy from the assets_candlestick_daily hypertable. Chunks already uploaded to object storage remain tiered.

Available functions

• add_tiering_policy(): create a policy to tier chunks older than a given interval
• remove_tiering_policy(): remove the tiering policy from a hypertable or continuous aggregate
• tier_chunk(): manually tier an individual chunk to object storage
• untier_chunk(): move a tiered chunk back to local storage
• disable_tiering(): disable tiering on a hypertable and remove its object storage catalog entries