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While Kafka excels at streaming data, the real challenge lies in making that data analytically useful without sacrificing consistency or performance. This talk explores why Apache Iceberg has emerged as the ideal streaming destination, offering ACID transactions, schema evolution, and time travel capabilities that traditional data lakes can't match. Learn about some foundational tools that enable streaming pipelines and why they all converge on this next-generation table format built for flexibility and scalability.

The next generation of streaming isn't about faster pipelines, but about smarter connections. DeltaJoin, a new operator in Apache Flink, reimagines stream joins by moving from brute-force state to change-driven computation. Paired with Fluss, Flink's purpose-built storage layer, it enables systems that are real-time, scalable, and cost-efficient. Anton will show how DeltaJoin and Fluss shift streaming architecture from ephemeral flows to durable, queryable state that bridges real-time processing with lakehouse patterns. Drawing on production experience, he'll demonstrate how these innovations reduce join costs, simplify architectures, and unlock new possibilities for real-time analytics. Attendees will leave with a vision of Flink 2.x as the backbone for event-driven systems and modern data platforms.

In this session, see how meshIQ, a comprehensive management and observability platform for messaging and event streaming technologies like Kafka, RabbitMQ and IBM MQ, can be used to track application message flows, help identify bottlenecks and locate "missing" messages.