Gonna Go Back in Time with Apache Iceberg

Apache Iceberg is quickly becoming the foundation of the modern Data Lakehouse, offering ACID guarantees, schema evolution, time travel, and multi-engine compatibility over cheap object storage. We’ll work with Iceberg hands-on and show how to build durable, versioned, trustworthy datasets directly from streaming pipelines.

You’ll see Flink writing to Iceberg, Kafka events flowing into governed tables, and how snapshots let you query “what the data looked like yesterday.” We’ll compact, rewind, evolve schemas, roll back mistakes, and even handle CDC-style updates — all in real time and all powered by open source.

Whether you’re building for Data Mesh, Lakehouse, or stream-batch unification, this talk will show you how to use Iceberg to defend your data and enable self-serve, analytical infrastructure at scale.

Set up a full Lakehouse pipeline with Kafka, Flink, Iceberg, and MinIO (S3 local clone)
Use Time Travel to query historical snapshots of your data
Run Compaction to optimize small files into efficient Parquet chunks
Perform Schema Evolution safely with zero downtime
Ensure Conflict-Free Streaming Writes with exactly-once guarantees
Expire and Roll Back Snapshots to recover from mistakes or manage retention
Apply CDC-style Merge/Upserts into Iceberg tables from change logs
If time remaining, explore other engines other than Flink, like Dremio or Trino

About Daniel Hinojosa

Daniel is a programmer, consultant, instructor, speaker, and recent author. With over 20 years of experience, he does work for private, educational, and government institutions. He is also currently a speaker for No Fluff Just Stuff tour. Daniel loves JVM languages like Java, Groovy, and Scala; but also dabbles with non JVM languages like Haskell, Ruby, Python, LISP, C, C++. He is an avid Pomodoro Technique Practitioner and makes every attempt to learn a new programming language every year. For downtime, he enjoys reading, swimming, Legos, football, and barbecuing.

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