IN-PERSON: Apache Kafka® x Apache Flink® x Apache Iceberg™

Join us for an Apache Kafka® meetup on May 13th from 6:00pm in Kraków hosted with our friends at VirtusLab! The talks will be presented in English.

📍Venue:
VirtusLab
Szlak 49, 31-153 Kraków, Poland

***
🗓 Agenda:

• 6:00pm: Doors open/Welcome
• 6:00pm - 6:10pm: Drinks & Networking
• 6:10pm - 6:50pm: Jan Siekierski, Data Streaming consultant, Kentra.io
• 6:50pm - 7:05pm: Drinks & Networking
• 7:05pm - 7:45pm: Viktor Gamov, Principal Developer Advocate, Confluent
• 7:45pm - 8:00pm: Additional Q&A & Networking

💡 Speaker One:
Jan Siekierski, Data Streaming consultant, Kentra.io

Title of Talk:
Stateless Kafka Brokers - comparison of technologies available in this space

Abstract:
A new category of software is emerging: Stateless Kafka Brokers. Warpstream started the race in August 2023, but today we have 5 more alternatives available.

I'll do an analysis of this category comparing architectures, features and performance.
Technologies covered: Warpstream, AutoMQ, Confluent Freight Cluster, Bufstream, StreamNative Ursa, Tansu

Bio:
After 12 years in the IT industry now I'm helping organizations get the most value out of Data Streaming.

💡 Speaker Two:
Viktor Gamov, Principal Developer Advocate, Confluent

Title of Talk:
One Does Not Simply Query a Stream

Abstract:
Streaming data with Apache Kafka® has become the backbone of modern day applications. While streams are ideal for continuous data flow, they lack built-in querying capability. Unlike databases with indexed lookups, Kafka’s append-only logs are designed for high throughput processing, not for on-demand querying. This necessitates teams to build additional infrastructure to enable query capabilities for streaming data. Traditional methods replicate this data into external stores such as relational databases like PostgreSQL for operational workloads and object storage like S3 with Flink, Spark, or Trino for analytical use cases. While useful sometimes, these methods deepen the divide between operational and analytical estates, creating silos, complex ETL pipelines, and issues with schema mismatches, freshness, and failures.

In this session, we’ll explore and see live demos of some solutions to unify the operational and analytical estates, eliminating data silos. We’ll start with stream processing using Kafka Streams, Apache Flink®, and SQL implementations, then cover integration of relational databases with real-time analytics databases such as Apache Pinot® and ClickHouse. Finally, we’ll dive into modern approaches like Apache Iceberg® with Tableflow, which simplifies data preparation by seamlessly representing Kafka topics and associated schemas as Iceberg or Delta tables in a few clicks. While there’s no single right answer to this problem, as responsible system builders, we must understand our options and trade-offs to build robust architectures.

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.

***
DISCLAIMER
NOTE: We are unable to cater for any attendees under the age of 18.
If you wish to speak at and/or host a future meetup, please email community@confluent.io