Apache Iceberg: The Definitive Guide

Chapter 13. Migrating to Apache Iceberg

Organizations are constantly seeking innovative solutions to manage their data more efficiently and effectively. Apache Iceberg has emerged as a powerful framework for data lakes, offering a high-performance table format that operates like a relational database management system (RDBMS) table. This chapter delves into the process of migrating your data architecture to leverage the benefits of Apache Iceberg.

Why would you migrate to Apache Iceberg?

You don’t have a data lakehouse or are using the Hive table format

Apache Iceberg will supercharge the data on your data lake with ACID transactions, schema/partition evolution, time travel, and more, effectively turning your data lake into a data lakehouse that gives you the flexibility of data lakes with the performance/features of data warehouses.

Iceberg offers unique benefits over other table formats

Apache Iceberg’s unique features include an open specification, open source libraries, transparent project governance, diversity in project governance, no vendor lock-in, and a diverse ecosystem.

While migrating to Apache Iceberg promises a more streamlined data architecture, the process itself, as with any migration, can be intricate and demanding. The transition involves adapting existing data structures, modifying data ingestion pipelines, and updating data processing workflows. Moreover, organizations may need to refactor existing data models and restructure data storage in Iceberg-compatible ...