Enterprise scale in-place migration to Apache Iceberg: Implementation guide

This article provides a comprehensive implementation guide for migrating enterprise-scale Parquet-based data lakes to Apache Iceberg format in-place, without data rewriting or duplication.

• Apache Iceberg enables ACID transactions, schema evolution, and point-in-time recovery for data lakes
• Two migration methodologies: migrate/register_table for Hive-registered tables and add_files for raw Parquet data
• DynamoDB serves as centralized control plane for tracking migration state, retries, and errors
• Migrate procedure converts Parquet tables to Iceberg; register_table registers in AWS Glue Data Catalog
• Add_files procedure imports existing Parquet files into empty Iceberg tables without physical movement
• Solution uses Amazon EMR, AWS Glue, and Amazon Athena for implementation
• State management tracks each dataset through migration stages with error auditing capabilities
• Non-Hive partitioned datasets require snapshot procedure instead of direct add_files approach
• Iceberg tables in AWS Glue/Athena are managed; DROP TABLE deletes both metadata and underlying data

This guide enables enterprises to modernize Parquet data lakes into Iceberg-powered lakehouses with automated, observable, fault-tolerant migration pipelines.