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TECHNICAL PAPER
CDC to Iceberg
4 Major Challenges, and How To Solve Them
This technical paper explores the complexities of implementing CDC with Apache Iceberg, specifically focusing on the key challenges that traditional CDC tools face and how you can overcome them.
From managing object store limitations to handling concurrent writes and snapshot amplification, this paper outlines the most difficult aspects of CDC in Iceberg environments and provides practical solutions for each.
What you will learn from this technical paper:
- The core challenges of applying CDC to Iceberg-based lakehouse.
- How to enforce primary key constraints and manages data quality.
- Strategies for improving merge-on-read performance with Iceberg.
- Techniques to resolve write conflicts and optimize snapshot management in real-time CDC implementations.
- And more...
Download Whitepaper
This whitepaper serves as a comprehensive resource for those looking to leverage Apache Iceberg in their data engineering and machine learning applications.
Who should read this guide?
- Data Engineers and Data Architects: Professionals focused on designing and optimizing data pipelines and storage solutions will find valuable insights into implementing Apache Iceberg to manage large-scale data efficiently.
- Technical Managers and CTOs: Decision-makers responsible for choosing technologies and planning data strategies will gain insights into the advantages of Iceberg over traditional data management solutions, supporting informed technology selection and investment.
- Database Administrators and Developers: Those managing and developing database systems can learn about Iceberg's approach to solving common issues related to data consistency, performance, and schema management.
