Architecting an Apache Iceberg Lakehouse

<p>Building a data platform can be difficult, and many systems are expensive to run. When you rely on one vendor, it can be hard to change or improve your setup later. A modern data platform should be reliable, able to grow with your needs, and not tied to costly licences. Open-source tools give you more control over how your platform works and how much you spend. This book shows a clear way to build a complete data platform using Apache Iceberg. </p> <ul> <li>Learn how to create a modular and scalable Iceberg Lakehouse architecture. </li> </ul> <ul> <li>Understand where Spark, Flink, Dremio, and Polaris fit into your design. </li> </ul> <ul> <li>Build reliable batch and streaming ingestion pipelines for your data. </li> </ul> <ul> <li>Apply strategies for governance, security, and performance at scale. </li> </ul> <ul> <li>Connect architectural theory with practical implementation through hands-on examples. </li> </ul> <p><strong>Architecting an Apache Iceberg Lakehouse</strong> is a practical guide to designing a complete data platform. The book carefully guides you through each layer of the architecture, from storage and ingestion to governance and security. It uses hands-on examples, such as ingesting data with Apache Spark and building dashboards in Apache Superset, to illustrate key concepts. </p> <p>After reading this book, you will understand how to design and build a data platform that can grow with your needs. It explains the key choices you need to make when working with large amounts of data in real projects. </p> <p>This book is written for data architects who already know the basics of data Lakehouses and are planning a new system or moving from an existing one. </p>