Talk by Nicoleta Lazar, Senior Data Engineer at Fresha.

At Fresha, we became the pioneers that put StarRocks to test in production for realtime analytical workloads. But one of the first challenges we faced was getting all the data there reliably and efficiently. We had to think about historical data, and realtime data and orchestrate all of that, such that we can move fast, without breaking too many things. Our tools of choice: Airflow, StarRocks Pipes, Apache Flink. In this talk, I’ll share how we built our data pipelines using Apache Flink and Airflow, what worked and what didn’t for us. Along the way, we’ll explore how Flink helps ensure data consistency, handles failures gracefully, and keeps our real-time workloads running strong.

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.

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.