Traditional architectural data designs are severely limited. To use these designs, you need to transfer data to each tool—a process that is costly and restricts the availability of warehouse features across all your data. This lack of flexibility forces you to tailor your workflow to the tool where your data is locked in, creating silos and fluctuations in data. This book shows you a better solution.

Apache Iceberg offers the capabilities, performance, scale, and economies that meet the promise of an open data lakehouse. By following the lessons of this book, you will be able to achieve interactive, batch, machine learning, and streaming analytics with this lakehouse. Authors Tomer Shiran, Jason Hughes, Alex Merced, and Dipankar Mazumdar from Dremio guide you through the process.

With this book, you will learn:

• The architecture of Apache Iceberg tables
• What happens behind the scenes when you perform operations on Iceberg tables
• How to further optimize Apache Iceberg tables for maximum performance
• How to use Apache Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio Sonar
• How Apache Iceberg can be used in streaming and batch ingestion

Discover why Apache Iceberg is a fundamental technology for implementing an open data lakehouse. Pages: 300, Dimensions: 17.8x17.8cm