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# Swapping a Data Warehouse at Runtime: Zero-Downtime Migration Without Changing a Single Client


- **Date:** Friday, Jul 10, 2026
- **Time:** 14:20–14:50 (30 min)
- **Room:** Stage 10 - powered by TikTok
- **Event:** World Congress 2026 Europe

## Recording

[Watch recording](https://www.wearedevelopers.com/videos/100311-swapping-a-data-warehouse-at-runtime-zero-downtime-migration-without-changing-a-single-client)

## Description

Trade Republic serves 10 million with €150 billion under management. Our data warehouse handles 4 million queries daily across analytics, product features, and the ML fraud detection that protects our customers. It replicates 220 databases into a 620 TB lakehouse. It cannot go down.

Moving to an open lakehouse architecture — Apache Iceberg & bring-your-own-compute  — "schedule a maintenance window" was not an option. Neither was asking hundreds of consumers — BI tools, pipelines, ML models, product services — to rewrite their connections.

The destination: decoupled storage-compute where teams choose the engine that fits their workload. Spark, Athena, DuckDB — all reading from the Iceberg. But the migration path matters as much as the destination.

Our approach: "Engy" build a protocol-compatible proxy that presents the exact wire interface of our existing warehouse. Every client connects the same way it always has. Behind that stable interface, we're free to change everything: swap compute engines, cache, add features — all invisible to consumers.

The key enabler is in-flight SQL transpilation. The proxy rewrites SQL, translates table references between catalogs, and normalises result, all in the request path. This gives us a multi-engine architecture with perfect interop.

Teams onboard without changing a driver, a connection string, or a line of code. We ship new engines and features behind the interface while production traffic is flowing — building the plane as we fly it. The interface becomes a contract that decouples the pace of infrastructure evolution from the pace of consumer adoption.

In this talk I'll walk through how we designed the Engy proxy interface for long-term stability that lets us migrate a 620 TB system query-by-query without downtime.

True to Trade Republic's engineering philosophy, the entire stack is built on open-source foundations — no vendor tooling, no proprietary middleware.

## Speakers

### [Max Fischer](https://www.wearedevelopers.com/@max-fischer)

Director Engineering at Trade Republic
### [Michael O'Toole](https://www.wearedevelopers.com/@michael-o-toole)

Data Staff Engineer at Trade Republic


## Related talks at this congress

- [TiDB, One Layer at a Time: How Distributed SQL Became an Agentic AI Backbone](https://www.wearedevelopers.com/events/world-congress-2026-europe/sessions/1119-tidb-one-layer-at-a) — Daniël van Eeden, Mattias Jonsson
- [The Migration Cookbook](https://www.wearedevelopers.com/events/world-congress-2026-europe/sessions/1167-the-migration) — Robert Lehmann
- [What If We've Been Scaling Stream Processing Wrong All Along?](https://www.wearedevelopers.com/events/world-congress-2026-europe/sessions/1313-what-if-we-ve-been) — Hartmut Armbruster
- [The Missing Layer Between Enterprise Data and AI Agents](https://www.wearedevelopers.com/events/world-congress-2026-europe/sessions/1328-the-missing-layer) — Jannis Eickenroth, Sebastian Klenke