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  • Book Overview & Buying Engineering Lakehouses with Open Table Formats
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Engineering Lakehouses with Open Table Formats

Engineering Lakehouses with Open Table Formats

By : Dipankar Mazumdar, Vinoth Govindarajan
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Engineering Lakehouses with Open Table Formats

Engineering Lakehouses with Open Table Formats

By: Dipankar Mazumdar, Vinoth Govindarajan

Overview of this book

Engineering Lakehouses with Open Table Formats provides detailed insights into lakehouse concepts, and dives deep into the practical implementation of open table formats such as Apache Iceberg, Apache Hudi, and Delta Lake. You’ll explore the internals of a table format and learn in detail about the transactional capabilities of lakehouses. You’ll also get hands on with each table format with exercises using popular computing engines, such as Apache Spark, Flink, Trino, and Python-based tools. The book addresses advanced topics, including performance optimization techniques and interoperability among different formats, equipping you to build production-ready lakehouses. With step-by-step explanations, you’ll get to grips with the key components of lakehouse architecture and learn how to build, maintain, and optimize them. By the end of this book, you’ll be proficient in evaluating and implementing open table formats, optimizing lakehouse performance, and applying these concepts to real-world scenarios, ensuring you make informed decisions in selecting the right architecture for your organization’s data needs.
Table of Contents (15 chapters)
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13
Other Books You May Enjoy
14
Index

Summary

Interoperability is emerging as a cornerstone of modern lakehouse architecture as organizations adopt multiple open table formats, each optimized for specific use cases. This chapter introduced how solutions such as Delta UniForm and Apache XTable are bridging the gaps between formats by enabling cross-engine reads, schema sync, and format translation.

We explored the architectural trade-offs, real-world use cases (such as CDC ingestion and cross-format ML pipelines), and current limitations, offering a practical lens into the evolving landscape of format interoperability in lakehouse systems.

In the next chapter, we will look at performance optimization techniques and how they help us in data analysis.

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