<p>What if SQL queries could process data as it is generated instead of after it is stored? Apache Flink speaks SQL fluently, but it is not a database - it is best understood as a conductor orchestrating endless streams of data rather than a librarian managing stored records.</p> <p>This session bridges the gap between traditional SQL and stream processing.</p> <p>In this session, Viktor Gamov will explore:</p> <ul> <li>The mental model shift: from “querying the database” to “continuously processing the stream,” using intuitive analogies</li> <li>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</li> <li>Table API: programmatic control with declarative simplicity, bridging SQL and full programming flexibility</li> <li>Flink AI: real-time feature engineering and model inference on streaming data using SQL-like patterns</li> <li>Real-world patterns: fraud detection during transactions, live analytics dashboards, and event-driven architectures</li> </ul> <p>Attendees will leave understanding not just how to use Flink SQL, but also when and why it transforms traditional database skills into real-time data superpowers.</p> <p>This session is ideal for SQL developers and data engineers ready to make their queries travel through time.</p>