Data Engineering Weekly · 2025-02-19 · 37 min
Fluss is a compelling new project in the realm of real-time data processing. I spoke with Jark Wu , who leads the Fluss and Flink SQL team at Alibaba Cloud, to understand its origins and potential. Jark is a key figure in the Apache Flink community, known for his work in building Flink SQL from the ground up and creating Flink CDC and Fluss. You can read the Q&A version of the conversation here, and don’t forget to listen to the podcast. What is Fluss and its use cases? Fluss is a streaming storage specifically designed for real-time analytics. It addresses many of Kafka's challenges in analytical infrastructure. The combination of Kafka and Flink is not a perfect fit for real-time analytics; the integration of Kafka and Lakehouse is very shallow. Fluss is an analytical Kafka that builds on top of Lakehouse and integrates seamlessly with Flink to reduce costs, achieve better performance, and unlock new use cases for real-time analytics. How do you compare Fluss with Apache Kafka? Fluss and Kafka differ fundamentally in design principles. Kafka is designed for streaming events, but Fluss is designed for streaming analytics.
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