Native Masking

With native masking, tag-based data masking policies run directly inside Snowflake or Databricks, without making API calls to ALTR through the external function. The biggest benefit of native masking over default masking (which uses the external function) is that this local execution improves performance because it does not rely on external calls to ALTR.

Note

For Snowflake: You can choose between native masking or the existing default masking, which uses an external function to call ALTR.

For Databricks: Native masking is built in and used automatically, since external function masking is not supported.

Native Masking versus Default Masking Function

The following table compares data masking using ALTR’s native masking versus default masking (the external function). For Snowflake, use this table to help determine which data masking method is the right fit for your needs.

	Native Masking	Default Masking
Pros	Improved query performance; more masking options	Supports real-time policy updates; supports near-real-time query audit logs; support for detokenization and format-preserving encryption
Cons	Policy updates may take time to apply; no near-time audits; no rate limiting, detokenization, or decryption	Reduced query performance; fewer masking options
Use cases	When performance is critical; when your masking rules are stable	When you need dynamic policy logic; when you need audit logs; when you need detokenization and/or format-preserving encryption