Streaming

Track Chairs : Yu Li, Xin Wang

Streaming data processing is a big deal in big data these days, businesses crave ever-more timely insights into their data, and what was once a ‘batch’ mindset is quickly being replaced with stream processing. More and more companies, small and large, are rethinking their architecture with real-time context at the forefront, and starting to build their streaming platforms with powerful open source engines such as Apache Flink, Apache Spark, Apache Kafka, Apache Pulsar, Apache Storm, Apache StreamPark (incubating), Apache Paimon (incubating) etc.

In this topic, you will not only learn about the practical experience of first-line users in applying these Apache projects to their in-production environment, but also the latest developments in the ecology of these Apache projects, and visions on where streaming technology is heading in the future.

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Accelerating Multi-stream Join by Stream Graph Computing Chinese Session Zhao Qingwen

Ant Group's Next Generation High SLA Streaming Computing System Built on Apache Technology Stack Chinese Session Xin Wang

Apache Flink 2.1: Continuing Evolution Toward Data + AI All-in-One Chinese Session Ron Liu

Apache Iceberg ingestion with Apache NiFi and Polaris English Session Lester Martin

Application of Apache Flink in China Telecom's Logging Scenario Chinese Session Yan Zuo

Disaggregated State Management In Apache Flink Chinese Session Zhaoqian (Zakelly) Lan

Event-Driven Agent: From Stream Processing to Agentic AI Framework Chinese Session Xintong Song

Flex: Unified Stream and Batch Vectorized Engine Chinese Session Jacky Lau

How to handle your Star schema in the Streamhouse world English Session Alexey Novakov

Practice of Apache Flink Real-time Computing in China Mobile Cloud Chinese Session LEI XIE

Practice of Flink Memory Governance at ByteDance Chinese Session Yiheng Tang

Queue, Process, Predict: Kafka’s New Era with Flink LLMs and Datalake English Session Shekhar Prasad Rajak

Real-Time Assurance Practices for Tencent Big Data Flink on Cloud-Native Hybrid Low-Priority Cluster Chinese Session Pengxiang Wang

Scalable Join & Aggregation with External State and Dynamic Tables Chinese Session Feng Jin

The Intelligent Evolution of Fully Managed Resource Management for Tencent's Real-Time Computing Chinese Session Zihao Chen

When Flink Meets Fluss: The Future of Streaming Warehouse Chinese Session Jark Wu