Excessive Snapshot Storage from High-Churn Snowflake Tables

Simar Arora

Service Category

Storage

Cloud Provider

Snowflake

Service Name

Database Storage (Time Travel and Fail-safe)

Inefficiency Type

Inefficient Storage Usage

Explanation

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.

Relevant Billing Model

Detection

Identify tables with high storage consumption relative to their current active data size.
Use transient tables or temporary tables where modification patterns (INSERTs, UPDATEs, DELETEs) to detect high-churn tables.
Review Time Travel retention settings at the table and account level to determine if default settings are unnecessarily long.
Estimate the ratio of historical snapshot storage versus active storage for key tables.
Confirm with application and data engineering teams whether frequent table modifications are necessary, or if design changes could reduce churn.

Remediation

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.

Relevant Documentation