​Apache Iceberg™ is Coming to Europe! 🌍

​Join us for the very first Apache Iceberg™ Meetup in Europe! Our first event is hosted in Amsterdam, co-hosted by Lakekeeper and Databricks.

​Can't join us in person? No worries—register anyway to receive the event recordings and stay connected with the community.

Also make sure to join our Slack Channel to stay up-to-date with future meetups in Europe!

​Agenda

​​17:00 - 18:00: Doors Open & Networking 💃
18:00: Welcome
18:05 - 18:55: 3 Talks:
- 🌟V3, what's coming and where we are
- 🌟Securing Shared Data in Apache Iceberg
- 🌟Building a Postgres data warehouse with Iceberg
18:55 - 19:20: Break
19:20 - 20:00: 2 Talks
- 🌟Stream fast and don’t break things
- 🌟Upgrade your infrastructure to Iceberg with dlt + Lakekeeper
20:00 - 21:00: More Networking 🕺

​Presentations

​​🌟V3 what's coming and where we are

In this talk Fokko will give a high level overview the upcoming Iceberg V3 features. A state of where we are today, what's next, and how you can be part of this!

​Fokko Driesprong is an open source enthusiast and father of three, living in Friesland up north in The Netherlands. Studied computer science at the University of Groningen and got caught by open-source software early in his career. He's a member of the ASF, and committer and PMC on Iceberg, Parquet and Avro.

🌟 Securing Shared Data in Apache Iceberg

​Apache Iceberg enables interoperability among compute engines, yet this openness introduces significant security challenges. In this session, we'll unpack Iceberg's layered security, looking at access points at the file, catalog, and engine levels. We'll also explore how open authentication standards like OAuth2 and open authorization tools such as OpenFGA and OPA help secure your data across engines.

​Christian Thiel is the creator of Lakekeeper, an Apache Licensed Iceberg REST Catalog. He’s a big believer in open standards like Apache Iceberg, which he sees as the backbone of today’s modern, composable Data & Analytics systems.

🌟 Building a Postgres data warehouse with Iceberg

​Marco Slot is a data management expert at Crunchy Data, where he designs advanced PostgreSQL-based products. He leads the Crunchy Data Warehouse project—an OLAP system built with Iceberg, DuckDB, and PostgreSQL extensions.

​🌟 Stream fast and don’t break things

​Streaming data into Iceberg is gaining traction in modern data platforms, but it brings challenges beyond typical batch processing. In this talk, we dive into best practices and advanced tips for building reliable, efficient streaming pipelines with Iceberg. We cover tricky aspects like the constant creation of small files and how Iceberg’s architecture amplifies their impact on performance and storage. You’ll learn practical ways to optimize partitioning and sorting, fine-tune write configurations, and manage compaction costs in high-throughput scenarios.

​Yuval Yogev started as an algorithms developer working for 2 years at Mobileye, developing image processing algorithms for self driving cars. After that I have been working at Sygnia, building high scale security analytics products, ingesting tens of TB per day. I love building new products and designing large data pipelines, enthusiastic about new technologies. Currently building a new product, focused on the open lakehouse architecture.

​🌟Upgrade your infrastructure to Iceberg with dlt + Lakekeeper

Many organizations are exploring Iceberg to avoid data duplication, minimize transformation costs, and connect diverse components like MDS warehouses with Python ML/LLM tooling. However, upgrading existing infrastructure without vendor lock-in remains a challenge.
In this talk, we’ll showcase an interoperable approach using dlt and Lakekeeper to modernize data infrastructure while keeping existing key components intact. Our reference architecture leverages Lakekeeper as a catalog, PyIceberg for writing, DuckDB as a query engine and dlt for moving data between new and existing components.

​Violetta Mishechkina is a Solutions Engineer at dltHub with a background in machine learning and data science. After starting out creating ML models, she shifted her focus to the practical challenges of MLOps—where model size, infrastructure, and data quality take center stage. At dltHub, she works closely with customers and developers to streamline production workflows.

​About Lakekeeper

​Lakekeeper is an Apache-Licensed (it's yours!), secure, fast and easy to use Apache Iceberg REST Catalog implementation written in Rust. With advanced permission management, a comprehensive UI and native Kubernetes integration Lakekeeper makes it easy to build open Lakehouses with Iceberg.

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​​About Databricks

​​Databricks is the data and AI company. More than 10,000 organizations worldwide — including Block, Comcast, Condé Nast, Rivian, Shell and over 60% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to take control of their data and put it to work with AI. Databricks is headquartered in San Francisco, with offices around the globe, and was founded by the original creators of Lakehouse and Apache Spark™.

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​Notes

​Apache Iceberg, Iceberg, Apache, Apache Spark, and the Apache Iceberg project logo are either registered trademarks or trademarks of The Apache Software Foundation. Copyright © 2025