Petabyte-Scale GDPR Deletion via Apache Iceberg Delete Vectors and Snapshot Expiration
Keywords:
Apache Iceberg, GDPR, snapshot expiration, positional delete, data lakehouse, petabyte-scale, compliance automationAbstract
This article explains how Apache Iceberg's delete vector and snapshot expiry can efficiently erase petabyte-scale GDPR-compliant data. We use positional delete files to hide personal data without database updates. Snapshot expiration frees up physical storage and improves analytic workload read performance utilising right-to-erasure. Delete plans run reliably and quickly using partition pruning and task-level parallelism. Despite fast snapshots and many operations in shared lakehouses, a validation framework verifies logical coherence and audit compliance. Synthetic multi-petabyte benchmarks indicate that the system can expand linearly, fulfil bulk deletion SLA requirements in under an hour, and recover space without compromising analytical queries. This method simplifies large-scale privacy-preserving data lakehouse administration.
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