Flex is designed to be a unified engine that supports both stream and batch processing, leveraging vectorization to maximize performance. Its goal is to seamlessly handle diverse data workloads, whether they are real-time streams or batch jobs, with high efficiency and scalability.

Speakers:

Jacky Lau: Expert in Distributed Computing Engines at Ant Financial, Calcite Committer and Flink Contributor

Expert in Distributed Computing Engines at Ant Financial, Calcite Committer and Flink Contributor with 10 years of Big Data development experience, focus on Flink/Spark/HBase