How to Achieve GDPR Compliance in PostgreSQL

How do I make my PostgreSQL database GDPR-compliant?

Use PostgreSQL features and SQL techniques to encrypt, anonymize, monitor, and delete personal data for GDPR compliance.

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Description

Example H2

Example H3

What GDPR obligations apply to a PostgreSQL database?

GDPR requires you to protect personal data, limit retention, allow user deletion requests, and keep audit trails. PostgreSQL can satisfy these rules with built-in encryption, row-level security, and logging.

How do I encrypt personal data at rest?

Enable pgcrypto or Postgres 16’s built-in encryption. Store only ciphertext in columns such as Customers.email. Keep keys in a Hardware Security Module (HSM) or environment variable outside the database.

UPDATE Customers SET email = pgp_sym_encrypt(email, :key) WHERE id = 42;

How can I anonymize historical records?

Create a view that masks or hashes fields once they exceed the legal retention window. Use generated columns or views so analytic queries still work without exposing raw data.

CREATE VIEW v_orders_gdpr AS SELECT id, customer_id, CASE WHEN order_date < CURRENT_DATE - INTERVAL '3 years' THEN '*** anonymized ***' ELSE total_amount::text END AS total_amount FROM Orders;

How do I implement the right to be forgotten?

Wrap DELETEs in a function that cascades through related tables, then VACUUM to purge pages. Maintain a deletion log for accountability.

BEGIN; DELETE FROM OrderItems WHERE order_id IN ( SELECT id FROM Orders WHERE customer_id = :cust_id); DELETE FROM Orders WHERE customer_id = :cust_id; DELETE FROM Customers WHERE id = :cust_id; COMMIT; VACUUM FULL;

How can I track data-access events?

Turn on log_statement = "mod" and send logs to an immutable store like S3. Use the pg_audit extension for column-level auditing in tables that hold personal data.

Best practice: automate compliance checks

Schedule cron jobs or CI pipelines that run SQL to find unencrypted columns, stale records, or missing indices. Alert when issues appear.

Why How to Achieve GDPR Compliance in PostgreSQL is important

How to Achieve GDPR Compliance in PostgreSQL Example Usage


-- Remove a customer and purge pages
SELECT forget_customer(42);
VACUUM FULL;

How to Achieve GDPR Compliance in PostgreSQL Syntax


-- Encrypt a column
UPDATE Customers
SET    email = pgp_sym_encrypt(email, 'my_secret_key')
WHERE  id = 42;

-- Mask data older than 3 years
CREATE VIEW v_orders_gdpr AS
SELECT id,
       customer_id,
       CASE WHEN order_date < CURRENT_DATE - INTERVAL '3 years'
            THEN '*** anonymized ***'
            ELSE total_amount::text END AS total_amount
FROM   Orders;

-- Right to be forgotten helper
CREATE OR REPLACE FUNCTION forget_customer(p_id INT) RETURNS void AS $$
BEGIN
    DELETE FROM OrderItems WHERE order_id IN (SELECT id FROM Orders WHERE customer_id = p_id);
    DELETE FROM Orders WHERE customer_id = p_id;
    DELETE FROM Customers WHERE id = p_id;
END;
$$ LANGUAGE plpgsql;

Common Mistakes

Storing encryption keys in the same database. This negates encryption. Fix by keeping keys in an HSM or secrets store.
Using TRUNCATE instead of DELETE for "right to be forgotten." TRUNCATE skips foreign-key checks and may wipe non-personal data. Use targeted DELETEs with cascading.

Frequently Asked Questions (FAQs)

Do I need pg_audit for GDPR?

pg_audit adds column-level read/write logs, meeting GDPR’s accountability mandate. While basic logging works, pg_audit makes evidence collection easier.

Will VACUUM FULL remove deleted data permanently?

Yes. VACUUM FULL rewrites tables, eliminating dead tuples that could otherwise be recovered from disk.

How can I test anonymization?

Create a staging copy of production, run anonymization scripts, and diff outputs. Automated tests ensure masking remains effective after schema changes.