The GDPR Right-to-Erasure (Article 17) presents a critical challenge for organizations managing petabyte-scale data lakes: how do you efficiently process millions of deletion requests while maintaining query performance, preserving audit trails for compliance, and avoiding operational disruption? Traditional data lake architectures force teams into impossible tradeoffs—either maintaining tombstone records that bloat storage and slow queries, or physically deleting data and losing the audit trail required by regulators.
Apache Iceberg's row-level delete capabilities and metadata architecture provide a sophisticated solution to this compliance challenge. This session demonstrates production-tested patterns for implementing GDPR-compliant data deletion at scale while maintaining both system performance and regulatory audit requirements.