Snowflake automatically maintains previous versions of data when tables are modified or deleted. For tables with high churn—meaning frequent INSERT, UPDATE, DELETE, or MERGE operations—this can cause a significant buildup of historical snapshot data, even if the active data size remains small. This hidden accumulation leads to elevated storage costs, particularly when Time Travel retention periods are long and data change rates are high. Often, teams are unaware of how much snapshot data is being stored behind the scenes.
Storage charges are based on the total volume of physical storage used, including active data, Time Travel snapshots, and Fail-safe copies. High-churn tables can inflate storage costs because each change creates additional snapshot data that is retained for the configured Time Travel period.
Optimize Time Travel retention settings: Reduce retention periods (e.g., from 90 days to 1 day) for high-churn tables where long recovery windows are not necessary. Periodically clone and recreate heavily churned tables to "reset" accumulated historical storage if appropriate. Regularly monitor table storage metrics to proactively manage and clean up storage waste in evolving datasets.
