Retention of stale data occurs when old, no longer needed records are preserved within active Snowflake tables. Without lifecycle policies or regular purging, tables accumulate outdated data. Because Snowflake’s compute charges are tied to how much data is scanned, retaining large volumes of inactive or irrelevant data can drive up both storage and query execution costs unnecessarily.
Snowflake charges for the total volume of data stored in active tables. Larger table sizes directly increase storage costs and can also indirectly increase compute costs, as queries must scan more partitions when processing larger datasets.
Implement data retention policies to regularly archive or delete records older than the required retention period (e.g., retain only 90 days of data if historical lookbacks are not needed beyond that) Collaborate with business, analytics, and compliance teams to validate acceptable data retention thresholds Purge old records to reduce table storage size and improve query performance by minimizing unnecessary data scans Monitor table growth rates and periodically reassess lifecycle settings to ensure alignment with business needs
