Iceberg Compaction and Fine-Grained Access Control: Performance Challenges and Solutions

Modern data lakes increasingly rely on Apache Iceberg for managing large analytical datasets, while organizations simultaneously demand fine-grained access control (FGAC) to secure sensitive data. However, combining these technologies can create unexpected performance bottlenecks that significantly impact query execution times. This article explores the technical challenges that arise when implementing FGAC on Iceberg tables and provides practical guidance for choosing the right processing engine for your use case.

Understanding Iceberg Compaction

Apache Iceberg is an open table format designed for huge analytical datasets. One of its core features is compaction — the process of combining smaller data files into larger, more efficient ones to optimize query performance and reduce metadata overhead.