Considerations using RLS policies - Amazon Redshift
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Considerations using RLS policies

Following are considerations for working with RLS policies:

  • Amazon Redshift applies RLS policies to SELECT, UPDATE, or DELETE statements.

  • Amazon Redshift doesn't apply RLS policies to INSERT, COPY, ALTER TABLE APPEND statements.

  • Row-level security works with column-level security to protect your data.

  • When your Amazon Redshift cluster was on the latest generally available version that supports RLS, but is downgraded to an earlier version, Amazon Redshift returns an error when you run a query on base tables with RLS policies attached. The sys:secadmin can revoke access from users that were granted restricted policies, turn off RLS on tables, and drop the policies.

  • When RLS is turned on for the source relation, Amazon Redshift supports the ALTER TABLE APPEND statement for superusers, users that have been explicitly granted the system permission IGNORE RLS, or the sys:secadmin role. In this case, you can run the ALTER TABLE APPEND statement to append rows to a target table by moving data from an existing source table. Amazon Redshift moves all tuples from the source relation into the target relation. The RLS status of the target relation doesn't affect the ALTER TABLE APPEND statement.

  • To facilitate migration from other data warehouse systems, you can set and retrieve customized session context variables for a connection by specifying the variable name and value.

    The following example sets session context variables for a row-level security (RLS) policy.

    -- Set a customized context variable. SELECT set_config(‘app.category’, ‘Concerts’, FALSE); -- Create a RLS policy using current_setting() to get the value of a customized context variable. CREATE RLS POLICY policy_categories WITH (catgroup VARCHAR(10)) USING (catgroup = current_setting('app.category', FALSE)); -- Set correct roles and attach the policy on the target table to one or more roles. ATTACH RLS POLICY policy_categories ON tickit_category_redshift TO ROLE analyst, ROLE dbadmin;

    For details on how to set and retrieve customized session context variables, see SET, SET_CONFIG, SHOW, CURRENT_SETTING, and RESET.

  • Changing session user using SET SESSION AUTHORIZATION between DECLARE and FETCH or between subsequent FETCH statements won't refresh the already prepared plan based on the user policies at DECLARE time. Avoid changing session user when cursors are used with RLS-protected tables.

  • When the base objects inside a view object are RLS-protected, policies attached to the user running the query are applied on the respective base objects. This is different from object-level permission checks, where the view owner's permissions are checked against the view base objects. You can view the RLS-protected relations of a query in its EXPLAIN plan output.

  • When a user-defined function (UDF) is referenced in a RLS policy of a relation attached to a user, the user must have the EXECUTE permission over the UDF to query the relation.

  • Row-level security might limit query optimization. We recommend carefully evaluating query performance before deploying RLS-protected views on large datasets.

  • Row-level security policies applied to late-binding views might be pushed into federated tables. These RLS policies might be visible in external processing engine logs.


Following are the limitations when working with RLS policies:

  • Amazon Redshift supports SELECT statements for certain RLS policies with lookups that have complex joins, but doesn't support UPDATE or DELETE statements. In cases with UPDATE or DELETE statements, Amazon Redshift returns the following error:

    ERROR: One of the RLS policies on target relation is not supported in UPDATE/DELETE.
  • Whenever a user-defined function (UDF) is referenced in a RLS policy of a relation attached to a user, the user must have the EXECUTE permission over the UDF to query the relation.

  • Correlated subqueries aren't supported. Amazon Redshift returns the following error:

    ERROR: RLS policy could not be rewritten.
  • RLS policies can't be attached to external tables and materialized views.

  • Amazon Redshift doesn't support datasharing with RLS. If a relation doesn't have RLS turned off for datashares, the query fails on the consumer cluster with the following error:

    RLS-protected relation "rls_protected_table" cannot be accessed via datasharing query.
  • In cross-database queries, Amazon Redshift blocks reads to RLS-protected relations. Users with the IGNORE RLS permission can access the protected relation using cross-database queries. When a user without the IGNORE RLS permission accesses RLS-protected relation through a cross-database query, the following error appears:

    RLS-protected relation "rls_protected_table" cannot be accessed via cross-database query.
  • ALTER RLS POLICY only supports modifying a RLS policy using the USING ( using_predicate_exp ) clause. You can't modify a RLS policy with a WITH clause when running ALTER RLS POLICY.

  • You can't query relations that have row-level security turned on if the values for any of the following configuration options don't match the default value of the session:

    • enable_case_sensitive_super_attribute

    • enable_case_sensitive_identifier

    • downcase_delimited_identifier

    Consider resetting your session’s configuration options if you attempt to query a relation with row-level security on and see the message "RLS protected relation does not support session level config on case sensitivity being different from its default value."

  • When your provisioned cluster or serverless namespace has any row-level security policies, the following commands are blocked for regular users:

    ALTER <current_user> SET enable_case_sensitive_super_attribute/enable_case_sensitive_identifier/downcase_delimited_identifier

    When you create RLS policies, we recommend that you change the default configuration option settings for regular users to match the session’s configuration option settings at the time the policy was created. Superusers and users with the ALTER USER privilege can do this by using parameter group settings or the ALTER USER command. For information about parameter groups, see Amazon Redshift parameter groups in the Amazon Redshift Management Guide. For information about the ALTER USER command, see ALTER USER.

  • Views and late-binding views with row-level security policies can't be replaced by regular users using the CREATE VIEW command. To replace views or LBVs with RLS policies, first detach any RLS policies attached to them, replace the views or LBVs, and reattach the policies. Superusers and users with the sys:secadmin permission can use CREATE VIEW on views or LBVs with RLS policies without detaching the policies.

  • Views with row-level security policies can't reference system tables and system views.

  • A late-binding view that's referenced by a regular view can't be RLS protected.

  • RLS-protected relations and nested data from data lakes can't be accessed in the same query.