Apache Iceberg™ NYC Community Meetup - Feb 2026
About the Event
Join us for an evening focused on Apache Iceberg, modern data architectures, and real-world experiences from teams building and operating data systems at scale.
This community-driven meetup brings together engineers and practitioners from Microsoft, Ryft, and Confluent to share architectural insights, practical lessons, and production perspectives around open data technologies.
Expect technical talks, open discussion, and plenty of time to connect with fellow data engineers, architects, and members of the NYC data community.
Tentative Agenda
6:00 – 6:30 PM: Drinks, food & networking
6:30 – 8:00 PM: Iceberg talks (Exact talk titles and agenda will be shared closer to the event)
8:10 – 8:45 PM: More drinks & networking
Iceberg Talks
• Talk 1 – Details TBA
• Talk 2 – Details TBA
• Talk 3 – Details TBA
Speakers & Talks
Roy Hasson / Sr. Director of Product, Microsoft
Roy is building products at Microsoft to help companies globally design, build and manage large scale data and AI projects, grounded in open source technology and industry standards.
LinkedIn: https://www.linkedin.com/in/royhasson
Substack: https://royondata.substack.com/
Viktor Gamov / Principal Developer Advocate, Confluent
Title: One Does Not Simply Query a Stream
Suppose you have embraced Apache Kafka as the core of your data infrastructure. In that case, you have probably integrated event-driven services to communicate with each other through topics, combined with legacy systems through an ecosystem of connectors, and responded more or less in real-time to things happening in the world outside your software. Immutable logs of events form a more robust backbone than the one-database-to-rule-them-all of your profound monolith past. Your stack is more evolvable, responsive, and easier to work with.
However, you might face a challenge now that everything is a stream - how do you query things? Although you may name at least one or two ways off the top of your head, it's time you think through how to make the choice.
In this talk, we'll explore the solutions currently in use for asking questions about the contents of a topic, including Kafka Streams, the various streaming SQL implementations, your favorite relational database, your favorite data lake, and real-time analytics databases like Apache Pinot. There is no single correct answer to the question, so as responsible builders of systems, we must understand our options and the trade-offs they present to us. You'll leave this talk even more satisfied that you've embraced Kafka as the heart of your system and are ready to deploy the right choice for querying the logs that hold your data.
Bio: Viktor Gamov is a Principal Developer Advocate at Confluent, founded by the original creators of Apache Kafka®. With a rich background in implementing and advocating for distributed systems and cloud-native architectures, Viktor excels in open-source technologies. He is passionate about assisting architects, developers, and operators in crafting systems that are not only low in latency and scalable but also highly available.
As a Java Champion and an esteemed speaker, Viktor is known for his insightful presentations at top industry events like JavaOne, Devoxx, Kafka Summit, and QCon. His expertise spans distributed systems, real-time data streaming, JVM, and DevOps.
Viktor has co-authored Enterprise Web Development from O'Reilly and Apache Kafka® in Action from Manning.
Follow Viktor on X – @gamussa to stay updated with Viktor's latest thoughts on technology, his gym and food adventures, and insights into open-source and developer advocacy.
Yuval Yogev / Co-founder & CTO, Ryft
Title: Implementing Intelligent Snapshot Management
Apache Iceberg snapshots enable time travel and rollback, but they are not free - What do you do when you can only afford to keep a few thousand of them?
With streaming ingestion, frequent commits, and compaction, tables can accumulate thousands of snapshots per day. Retention quickly becomes expensive without actually preserving useful restore points.
This session dives into how we implemented intelligent snapshot management. We present time-aware retention models that preserve what matters: high-resolution snapshots for recent history, and calendar-aligned restore points for long-term recovery. Instead of treating snapshots as temporary logs or hoarding them indefinitely, we apply backup patterns from databases and filesystems - leveraging Iceberg’s native snapshot and tagging semantics to make retention predictable, and operationally sustainable.
Bio: I’m passionate about building high-throughput distributed systems and making complex data platforms simple, resilient, and scalable. Today, I’m the Co-Founder and CTO of Ryft focused on next-generation data infrastructure. Before that, I spent several years as Chief Architect at Sygnia, helping companies strengthen their cyber resilience through scalable platforms and fast data pipelines.
Ryft Blog: https://www.ryft.io/blog
Ryft LinkedIn: https://www.linkedin.com/company/ryft/