Apache Fluss and Paimon：Fluss delivers sub-second real-time data for Flink (reducing state bloat); Paimon is a streaming lakehouse format with ACID and minute-level latency.
Alibaba Cloud presents key optimizations in Flink-Paimon real-time lakehouse architecture, including the Variant data type for efficient semi-structur...
TikTok transitioned to a unified Lakehouse architecture, powered by Apache Paimon, to optimize large-scale recommendation models (LRMs) that utilize user behavior sequences.
Learn how Apache Flink CDC accelerates real-time data ingestion in modern lakehouse architectures, enabling seamless and efficient data processing.
Discover Apache Paimon: real-time lake storage with Iceberg compatibility, optimized for streaming and multimodal AI applications.
Explore Apache Flink's Materialized Table for unified stream-batch ETL. Learn declarative data processing and overcome Lambda architecture challenges.
Discover vivo's real-world Lakehouse integration using Apache Paimon. Learn architecture design, performance optimization, and unified stream-batch processing.
Master Flink 2.1 SQL's AI functions with ML_PREDICT, Delta Join optimizations, and real-time AI integration for scalable stream processing applications.
Discover Apache Flink's evolution from real-time data processing to AI applications. Learn about Streaming Lakehouse, Apache Paimon, and Flash engine for next-gen AI.
Discover how China's booming EV market leverages Alibaba Cloud's Flink & Apache Paimon for real-time data processing.
Discover how Lalamove developed a scalable, cost-effective cloud-native streaming platform, leveraging Apache Flink and Paimon to enhance data management.
Explore how Apache Paimon addresses big data system challenges by offering a unified data lake storage solution.
Discover how to harness streaming data for AI-driven applications using Apache Flink, based on insights from the Flink Forward Asia 2024 keynote by Ashish Sharma and Ganireddy Jyothi Swaroop.
This article introduces a data processing workflow that integrates Realtime Compute for Apache Flink, EMR Serverless Spark, and Apache Paimon to enable real-time data ingestion.
Unified batch and stream processing of Flink is a well-established concept in the stream computing field.
This article is based on the keynote speeches given by LI Jinsong, WU Xiangping, DI Xingxing, and WANG Yunpeng during Flink Forward Asia 2023.
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.
Discover Apache Paimon: the solution for real-time data processing, seamlessly integrating Flink & Spark for streaming & batch operations.
The article introduces the development history, main scenarios, technical principles, performance tests, and future plans of the StarRocks + Apache Paimon lakehouse analysis.
Learn about Apache Flink, a distributed data processing engine for real-time analytics. Explore its features, use cases, and comparisons with other frameworks like Kafka and Spark.
