This article is adapted from Lincoln Lee’s presentation in the Real-Time AI track at Flink Forward Asia Singapore 2025.
Follow the Apache Flink® Community for making Flink's External System Data Processing More Efficient.
Traditional streaming data pipelines often need to join many tables or streams on a primary key to create a wide view.
This article is compiled from the presentation by Xu Yu, an internet big data expert at vivo and Apache Paimon Committer, during the Flink Forward Asia 2024 Streaming Lakehouse session (Part One).
Follow the Apache Flink® Community for making Stream Aggregation Simpler in Table API.
Follow the Apache Flink® Community for making Data Backup Simpler in Flink.
Follow the Apache Flink® Community for making Non-Partitioned State Scalable in Flink.
This tutorial demonstrates how to build a real-time MySQL-to-Kafka data pipeline using Flink CDC YAML without coding.
This article introduces Flink SQL, a unified stream-batch processing engine, focusing on key concepts like Stream-Table Duality, event time/watermarks.
Follow the Apache Flink® Community for making Flink Metrics More Accessible Through Web UI Visualization.
This is Technical Insights Series by Perry Ma | Product Lead, Real-time Compute for Apache Flink at Alibaba Cloud.
Apache Flink is a stream processing framework with two main interfaces: Flink SQL, which uses SQL for batch and streaming data, and the DataStream API...
This article is authored by the data pipeline team of Alibaba Cloud's open-source big data platforms.
This article is based on a presentation by Mr. Wang Feng (nickname: Mowen), senior director at Alibaba Cloud and head of the open source big data de.
Article emphasizes real-time data processing's importance in retail/e-commerce for tailored recommendations, highlighting Apache Flink's pivotal role.
In this demo, we'll guide you through creating a high-performance, cost-effective data warehouse solution for real-time analytics.
Today, we are excited to introduce Fluss, a cutting-edge streaming storage system designed to power real-time analytics.
Uncover the advancements from Apache Hive to Hudi and Iceberg in stream computing, as our expert navigates the transformative landscape of real-time data lakes.
Change Data Capture (CDC) detects and captures data changes as they occur in source systems, such as databases or applications.
This article is based on a keynote speech given by Jark Wu, head of Flink SQL and Flink CDC at Alibaba Cloud, during Flink Forward Asia 2023.
