Apache Iceberg Meetup: New Trends in Streaming and Data Analytics 2025
Join us for an incredible evening of insights, innovation, and community as we dive deep into the world of Apache Iceberg.Whether you’re an engineer, architect, or anyone working with Apache Iceberg, Kafka, or Flink. It’s your chance to dive into Apache Iceberg innovations alongside AutoMQ and Decodable - join our live session brimming with actionable insights for streaming and data lakehouse workflows.
📅 Event Details
Date & Time: July 24th, 9:00am PDT | 12:00pm EDT | 5:00pm BST
Format: live (YouTube & Zoom)
Please note that the Zoom meeting has a quota limit of 100 seats, available on a first-come, first-served basis.
In the meantime, we will live stream the event on AutoMQ’s official YouTube channel: https://www.youtube.com/@AutoMQ. You can watch the live broadcast there.Language: English
📍 How to Join
Free to attend, but registration is mandatory - this is a way to receive the YouTube live stream link (sent to your email pre-event) and updates.
🗓️ Agenda Highlights
➡️ 9:00 – 9:30 AM
Building Kafka on S3: Challenges and Solutions for Seamless Iceberg Integration
By Xinyu Zhou, Co-Founder & CTO at AutoMQ
In this part, we will explore the challenges of building a stream storage system like Kafka on top of S3 and how AutoMQ addresses these challenges while providing seamless integration with Iceberg. We will cover key aspects such as latency, IOPS, data fetch efficiency, metadata management, and throughput restrictions. Additionally, we will discuss how AutoMQ leverages Iceberg for schema management and efficient data organization, ensuring a cost-effective and scalable solution for managing data in the cloud.
➡️ 9:30 – 10:00 AM
Incremental Change Processing with Apache Flink and Iceberg
By Sharon Xie, Head of Product at Decodable
Apache Iceberg powers large-scale data lakehouses, but its limited CDC (Change Data Capture) support in V2 complicates incremental updates and deletes. This session breaks down pragmatic workarounds using Apache Flink: writing change streams as append tables, navigating trade-offs between append and upsert modes, and choosing the right strategy for your workload. Plus, get an exclusive preview of Iceberg V3’s native CDC support and how it will redefine real-time pipeline design.
✨ Why Attend?
Actionable insights from Iceberg, Kafka, and Flink experts
Peer networking to swap pipeline strategies
Live Q&A to solve your specific challenges
Early access to Iceberg V3’s game-changing features
Don’t miss this chance to level up your data systems expertise with the Apache Iceberg community!