Having been a key member of a large-scale migration from Apache Hudi to Delta Lake for a major investment-industry client, I’ve seen firsthand how complex today’s lakehouse table-format landscape has become. As architectures mature, the competitive focus has sharpened—most visibly in the rapidly accelerating race between Apache Iceberg and Delta Lake to define the next generation of open data management standards. Yet despite the momentum around Iceberg and Delta, Apache Hudi remains deeply entrenched in many organizations, powering long-standing, high-throughput ingestion and CDC-driven pipelines.

This session offers a clear, vendor-neutral comparison of Iceberg, Delta Lake, and Hudi, unpacking the architectural differences and real-world trade-offs across schema evolution, ACID transactions, incremental processing, indexing, and engine interoperability. We will go beyond feature comparisons to examine a critical and often underestimated challenge: migrating production data from Hudi to Iceberg or Delta. Drawing on real enterprise experience, we will highlight practical obstacles such as metadata translation, pipeline rewrites, operational continuity, table layout changes, and governance implications.

Attendees will leave with a pragmatic understanding of why industry conversations tend to center on Iceberg vs. Delta, why many companies still rely heavily on Hudi, and what it truly takes to execute a successful migration. The session provides both a strategic decision framework and grounded lessons learned from real-world, large-scale implementations.