---
type: note
tags: [code, security, database, note]
created: 2025-12-19T11:10:18.005+00:00
updated: 2026-01-02T01:39:32.364Z
---# Row-Level Security (RLS)

Row-Level Security (RLS) is a data security feature that restricts access to specific rows within a database table based on user attributes such as roles, permissions, or other criteria.
 It ensures that users can only view or modify data pertinent to their responsibilities, enhancing data privacy and security.
 RLS operates by applying security policies directly to data rows, which are evaluated automatically when a user executes a query, returning only the rows that meet the policy conditions.

This approach is particularly valuable in scenarios requiring fine-grained access control, such as multi-tenant environments where different clients must access only their own data, or in regulated industries like finance and healthcare, where sensitive information must be protected.
 For example, a financial institution can use RLS to restrict customer records to specific departments, while healthcare providers can ensure that only the medical staff involved in a patient’s care can access their records.

RLS complements other security mechanisms like column-level or role-level security by providing more granular control at the data row level.
 It can be implemented within various database platforms, including Microsoft SQL Server 
 , PostgreSQL 
 , Snowflake 
 , Teradata 
 , and cloud-based services like Power BI 
 and Tableau.
 In Power BI, RLS is implemented using roles, DAX filters, and user assignments, allowing administrators to define which data each user or group can see based on their identity.

RLS can be configured in static or dynamic forms. Static RLS uses hardcoded filters for fixed user groups, while dynamic RLS leverages functions like USERPRINCIPALNAME() or USERNAME() combined with mapping tables to apply filters based on real-time user context.
 Dynamic RLS is more scalable and suitable for large or evolving user bases.

Despite its benefits, RLS requires careful design and testing to avoid misconfigurations that could lead to data leaks or unauthorized access.
 It may also introduce performance overhead, as each query must be evaluated against the defined policies.
 However, when properly implemented, RLS provides a robust mechanism for enforcing data access controls directly within the database, reducing reliance on application-level logic and minimizing the risk of accidental data exposure.


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**Keywords:** code, security, database, note
