The Open Source Lakehouse: Architecting the Decoupled Analytical Foundation
Published by Self-published · Tech
Covers building a fully decoupled lakehouse using open source technologies, emphasizing modularity and vendor independence.
Who this book is for
Data engineers building pipelines, architects planning a platform migration, and technical leaders weighing the strategic implications of adopting open source data infrastructure.
Table of contents
- The Open Source Lakehouse Vision
- Apache Parquet: The Storage Foundation
- Apache Arrow: The In-Memory Standard
- Apache Arrow Flight: High-Performance Data Transfer
- Apache Iceberg: The Table Format
- Apache Iceberg: Advanced Operations
- Apache Polaris: The Open Catalog
- How the Stack Fits Together
- Multi-Engine Interoperability
- Building the Platform Yourself
- How Dremio Unifies the Stack
- Reference Architectures and Decision Frameworks
Excerpt
The modern data landscape is undergoing a profound structural transformation. For decades, organizations stored their analytical data inside proprietary systems controlled by a small number of dominant vendors. The data formats were closed. The query engines were closed. The governance policies were embedded inside opaque administrative consoles that only the vendor fully understood. Switching platforms meant migrating petabytes of data through narrow export pipelines, a process so expensive and risky that most organizations simply accepted annual price increases as the cost of doing business.
