The Modern Data Stack: Managing Iceberg Lakehouse

חשוב! שימו לב יש להרשם לאירוע בלומה דרך הלינק הבא: להרשמה ושריון מקום לחצו כאן

Date: Wednesday, January 28, 2026
Time: 18:00–20:00
Location: Tikal Offices, Tel Aviv

*The meetup will be held in Hebrew
*Registering through the link above is an application for approval and will be reviewed by our team before tickets are confirmed.

As data ecosystems evolve, the transition to a Lakehouse architecture has become the standard for organizations seeking flexibility and scalability. But how do you manage it correctly without being tethered to unpredictable cloud costs or getting lost in file management?
In this meetup, we’ll explore the practical side of managing an Iceberg Lakehouse – from building a 100% open-source stack to achieving optimal compaction in Apache Spark. We’ll dive into how to maintain high performance, keep your data organized, and stay in full control of your metadata.

18:00–18:30 → 🍕 Welcome Drinks & Networking
18:30–19:15 → Escape the Clouds: Building a Pure Open Source Lakehouse// Yoav Nordmann, Backend Architect, Tech & Group Lead @ Tikal
Are you tired of vendor lock-in and the unpredictable costs of proprietary data warehouses? Join us for a deep dive into building a 100% open-source data stack that doesn't compromise on performance. We will start by constructing a high-performance warehouse including compute, storage, and observability, then expand into a full-scale Lakehouse. Learn how to integrate Apache Iceberg and manage it with cutting-edge tools, ensuring you own your data, metadata, and compute-without the "cloud tax."

19:15–20:00 → Getting Compaction Right in Apache Spark // Ehud Eliaz, Chief Architect and Co-Founder @ DualBird
Compaction is a fundamental operation in Spark-based data lakes, yet getting it right is far from trivial. This talk breaks down how compaction is actually performed in Apache Spark and how it is used with open table formats like Apache Iceberg. We’ll focus on the practical side of running compaction at scale: critical configuration choices, Spark's behavior during runtime, and where performance issues tend to appear. Walk away with a clear picture of what “good” compaction looks like in real-world systems.

Important Note: To help us prepare for seating, please complete your registration on Luma. Registration via Meetup is for promotional purposes and will not guarantee entry.
🔗 Registration Link: https://tkl.to/tikal-m-meetup-28-1-26