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Book Overview & Buying
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Table Of Contents
Engineering Lakehouses with Open Table Formats
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The promise of the lakehouse architecture lies not just in its conceptual elegance but in its ability to solve real-world data challenges at scale. In this final chapter, we move from theory to practice by walking through three hands-on implementations of commonly seen use cases, each powered by an open table format best suited for the job.
These use cases will reflect common workflows in the analytics realm, ranging from analytical workloads (BI) and real-time ingestion to machine learning pipelines, and show how open source lakehouse-native tools and patterns such as write-audit-publish (WAP), incremental processing, and change data capture (CDC) can be put into action.
Each use case will demonstrate the following: