A presentation at Current London in in London, UK by Viktor Gamov
Stream Processing Smackdown: Apache Flink v Kafka Streams fl Viktor Gamov, Con uent X/Bluesky: @gamussa Current London, 2025
Viktor GAMOV Principal Developer Advocate @ConfluentInc Java Champion Co-Author «Kafka in Action» X and Bluesky: @gamussa
Slides and Video https://speaking.gamov.io/ X/Bluesky: @gamussa
What is Stream Processing? X/Bluesky: @gamussa
What is Stream Processing? Stream Processing is the toolset for dealing with events as they move! X/Bluesky: @gamussa
Stateless or Stateful? X/Bluesky: @gamussa
X/Bluesky: @gamussa
X/Bluesky: @gamussa
Application/System Architecture X/Bluesky: @gamussa
Kafka Streams Architecture X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
Apache Flink Architecture X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
State Management X/Bluesky: @gamussa
State Management in Kafka Streams X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
State Management in Apache Flink X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
Task Assignment and Scale X/Bluesky: @gamussa
Task Assignment and Scale in Kafka Streams X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
State Management in Apache Flink X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
Window Operations X/Bluesky: @gamussa
Windowing in Kafka Streams X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
Windowing in Apache Flink X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
Exactly Once X/Bluesky: @gamussa
Exactly Once in Kafka Streams X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
@gamussa | @kafkastreams | @apacheflink
@gamussa | @kafkastreams | @apacheflink
Exactly Once in Apache Flink X/Bluesky: @gamussa
@gamussa | @kafkastreams | @apacheflink
@gamussa | @kafkastreams | @apacheflink
Cool Story, Bro ™ But What Shall I Use? X/Bluesky: @gamussa
Use Kafka Streams • Event Driven Microservice • Flexible Deployment Model (just a jar) • Easy Testing • Built-in Exactly-Once Semantics • Kafka-centric X/Bluesky: @gamussa
Use Apache Flink • Massive Stateful Operations • Variety of Sources and Sinks • Uni ed API for Streams and Batch • Complex Window operations and Late Event handling • Flink SQL, PyFlink fi X/Bluesky: @gamussa
As Always Have a Nice Day X/Bluesky: @gamussa Github: @gamussa LinkedIn: vikgamov https://gamov.dev/rel http://gamov.dev/YouTube X and Bluesky: @gamussa
Attention, Data Streaming Engineers! In a world where speed is everything, choosing the proper stream processing framework is crucial. Want to supercharge your apps with real-time data processing? Should you opt for the streamlined Kafka Streams, a lightweight library for building streaming applications, or the feature-rich Apache Flink, a powerful and flexible stream processing framework? Viktor Gamov, a principal developer advocate at Confluent with extensive experience in stream processing, will walk you through the nuts and bolts of these two leading technologies. Through live coding and practical examples, we’ll cover:
• Mastering State Management: Discover how each framework handles stateful computations and pick up optimization tips. • Fault Tolerance in Practice: See how Kafka Streams and Flink keep your applications running smoothly, even when things go wrong. • Scalability Showdown: Find out which tool scales better under heavy loads and complex tasks. • Integration Insights: Learn how to seamlessly fit these frameworks into your existing setup to boost productivity. We’ll explore scenarios showcasing each option’s strengths and weaknesses, giving you the tools to choose the best fit for your next project. Whether you’re into microservices, event-driven systems, or big data streaming, this talk is packed with practical knowledge that you can immediately apply to your projects, improving performance and efficiency.
The following code examples from the presentation can be tried out live.
The following resources were mentioned during the presentation or are useful additional information.
