PostgreSQL Anonymizer

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Introduction

PostgreSQL Anonymizer is an extension to mask or replace personally identifiable information or commercially sensitive data in a PostgreSQL database, according to its documentation. Masking rules are declared with SQL security labels directly in the database schema, so the rules live next to the data definition.

The docs describe several masking methods: static masking permanently replaces data, dynamic masking hides data only for masked roles, replica masking provides an anonymised replica, anonymous dumps export masked data, and masking views and data wrappers offer further options. Functions cover fake data, randomisation, partial scrambling, noise, generalisation and more, and features such as privacy by default, sampling and identifier detection help cover sensitive columns.

The project is developed by Dalibo on GitLab. Release 3.3.2 shipped in October 2026.

In the quality loop it supports safe test and analytics databases.

Features

1. Declarative rules: Security labels in the schema.
2. Static and dynamic masking: Permanent or role-based.
3. Anonymous dumps: Export masked data.
4. Masking functions: Fake, random, partial, noise, generalisation.
5. Privacy by default: Mask unlabelled columns.

Pros

1. In-database: Rules live with the schema.

Cons

1. PostgreSQL only: Extension must be installed.
2. Managed database limits: Check if your provider allows the extension.

Usage and Links (Example)

CREATE EXTENSION anon;
SECURITY LABEL FOR anon ON COLUMN customer.email IS 'MASKED WITH FUNCTION anon.fake_email()';
SELECT anon.anonymize_database();

Resources:

• PostgreSQL Anonymizer website

Pricing

Free and open source (PostgreSQL Licence).

Recommended for?

1. PostgreSQL teams needing in-database masking.
2. Not a fit for other databases.

Conclusion

PostgreSQL Anonymizer is a mature, declarative masking extension for PostgreSQL.

On CheckOps, PostgreSQL Anonymizer is filed under the Integration testing and Security testing stages. Related tools listed here include Greenmask, Tonic Structural, Delphix, DATPROF, K2view Test Data Management and Synthesized. Before choosing, compare them on licence, supported languages and platforms, hosting model, and how well each fits your existing CI pipeline. Facts on this page were checked against the official website, documentation and repository on 11 November 2026; statements the vendor makes about its own product are marked as vendor claims.