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” and “Apache Kafka® in Action”. 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.
What if your SQL queries could process data as it happens instead of after it’s stored? Apache Flink speaks SQL fluently, but it’s not a database – think of it as a conductor orchestrating endless streams of data rather than a librarian managing stored records.
This session bridges the gap between traditional SQL and stream processing.
We’ll explore:
The Mental Model Shift – From “query the database” to “continuously process the stream” using intuitive analogies Flink SQL in Action: How familiar operations like SELECT, JOIN, and GROUP BY work on infinite data streams, plus temporal joins, time windows, and watermarks Table API: Programmatic control with declarative simplicity, bridging SQL and complete programming flexibility Flink AI: Real-time feature engineering and model inference on streaming data using SQL-like patterns Real-World Patterns: Fraud detection during transactions, live analytics dashboards, and event-driven architectures You’ll leave understanding not just how to use Flink SQL, but when and why it transforms traditional database skills into real-time data superpowers.
Perfect for: SQL developers and data engineers ready to make their queries travel through time.