Name: IN-PERSON; Apache Kafka® Meetup
Start: 2025-11-27T17:00:00+01:00
End: 2025-11-27T20:00:00+01:00
Location: mesoneer AG

Join us for an Apache Kafka® meetup on Thursday, November 27th from 5:00pm in Zurich hosted by mesoneer!

📍**Venue:**
mesoneer AG, Richtistrasse 17, 8304 Wallisellen, Switzerland

🗓 **Agenda:**

* 5:00pm: Doors open
* 5:00pm – 5:30pm: Snacks, Drinks and Networking
* **5:30pm – 6:00pm: Ralph Debusmann, Lead Enterprise Kafka Engineer, Migros-Genossenschafts-Bund**
* **6:00pm - 6:30pm: Talk 2 TBA**
* **6:30pm - 7:00pm: Talk 3 TBA**
* 7:00pm - 9:00pm: Additional Q&A, Networking and Pizza

💡 **Talk 1:**
Ralph Debusmann, Lead Enterprise Kafka Engineer, Migros-Genossenschafts-Bund

**Title of Talk:**
Kafi Streams - Complex Stream Processing on Python Without the Complexity\*

**Abstract:**
In this talk, I will unveil the very first prototype of Kafi Streams, an Open Source stream processing libary built on top of PyDBSP, a pure Python implementation of Feldera's novel "Database Stream Processing" theory.

Why would we need another stream processing library? One whose name sounds so strikingly similar to the most popular stream processing library on the planet (ok, not for Python that is)?

Because existing stream processing libraries are complex, even Kafka Streams. You cannot easily do stream processing without understanding concepts like streams, tables, co-partitioning, windowing (hopping, tumbing, sessions...), state stores etc. You cannot possibly correctly use Kafka Streams as someone who is not a streaming expert.

On the contrary, Kafi Streams aims at making stream processing simple. As in - complex stream processing without the complexity. Anyone, even those who have never used streaming before, should be able to do it. Right from the start. Because with DBSP as our basis, streaming is not different from batch any longer. It is all the same.

**Bio:**
Ralph Debusmann is the Lead Enterprise Kafka Engineer at Migros-Genossenschafts-Bund, where he is driving the integration of the vast variety and volume of data generated across the organization into a real-time streaming data mesh based on Apache Kafka. His primary focus is on enabling scalable data-sharing solutions that support real-time decision-making and analytics across different business units at Migros.

💡 **Talk 2:**
TBA

**Title of Talk:**
TBA

**Abstract:**
TBA

**Bio:**
TBA

💡 **Talk 3:**
TBA

**Title of Talk:**
TBA

**Abstract:**
TBA

**Bio:**
TBA

\*\*\*
DISCLAIMER
We are unable to cater for any attendees under the age of 18.
If you would like to speak or host our next event please let us know! [[community@confluent.io](http://community@confluent.io/)](http://community@confluent.io/)

Alice Richardson

Maximilian Walser

Zürich Apache Kafka® Meetup by Confluent

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Zürich Apache Kafka® Meetup by Confluent

IN-PERSON; Apache Kafka® Meetup

Zürich Apache Kafka® Meetup by Confluent

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