Compliance & Privacy (GDPR, CCPA)

This pattern centers on user-scoped datasets, exportability, and controlled retention/deletion.

Core pattern

• USER table scope for per-user data boundaries
• storage routing (STORAGE_ID, optional USE_USER_STORAGE) for compliance regions
• role-based access checks to reduce accidental cross-user exposure
• auditable row metadata (CURRENT_USER(), timestamps)

Example Schema

CREATE TABLE app.user_data (
  id BIGINT PRIMARY KEY DEFAULT SNOWFLAKE_ID(),
  data_type TEXT,
  content JSON,
  created_by TEXT DEFAULT CURRENT_USER(),
  created_at TIMESTAMP DEFAULT NOW()
) WITH (
  TYPE = 'USER',
  STORAGE_ID = 'local',
  USE_USER_STORAGE = true,
  FLUSH_POLICY = 'interval:300'
);

Example workflow

# 1) Query user records for export package
# 2) Serialize records to archive
# 3) Deliver export artifact with audit metadata

-- Account deletion path (application-owned workflow)
DROP USER 'alice';

Code references

• Table option semantics (STORAGE_ID, USE_USER_STORAGE): table_options.rs 
• Permission model by table type and role: permissions.rs