This article introduces an Alibaba Cloud reference architecture for real-time, multi-tenant productivity tracking of distributed engineering teams.
This article examines how Alibaba Cloud RocketMQ functions as the message buffer layer between IoT Platform and downstream consumers, enabling durable...
This article examines how Alibaba Cloud's IoT Platform, Realtime Compute for Apache Flink, MaxCompute, and DataV form a complete, scalable pipeline fr...
Version 0.3 aims to enhance capabilities with features like Agent Skills Integration, Mem0 based Long-Term Memory support and Durable Execution Reconciler.
Data engineers: Discover 5 key trends shaping the AI-native era with Alibaba Cloud. AI’s 2025 shift demands unified, real-time, multimodal infrastructure.
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.
Discover how Delta Join in Apache Flink revolutionizes stream processing, reducing state and costs while boosting performance and stability.
Today, we are excited to introduce Fluss, a cutting-edge streaming storage system designed to power real-time analytics.
Learn Apache Flink FLIP-15 smart iterations with StreamScope and intelligent termination. Master backpressure optimization, deadlock prevention, and advanced loop processing for real-time analytics.
From the 2025 Apsara Conference: Alibaba Cloud debuts major Realtime Compute for Apache Flink upgrades in computing, storage, and real-time AI integration.
Alibaba Cloud presents key optimizations in Flink-Paimon real-time lakehouse architecture, including the Variant data type for efficient semi-structur...
Apache Flink Agents: A landmark collaboration to build a scalable, production-grade framework for event-driven streaming agents powered by Apache Flink.
FLIP-18: Boost Flink's sorting efficiency with code generation, optimizing memory access and byte order handling.
FLIP-17 introduces side inputs to Apache Flink's DataStream API for more flexible and efficient stream processing with auxiliary data.
FLIP-16 explores and addresses the challenges of reliable iterative stream processing in Flink, highlighting memory, complexity, and performance issue.
TikTok transitioned to a unified Lakehouse architecture, powered by Apache Paimon, to optimize large-scale recommendation models (LRMs) that utilize user behavior sequences.
This article introduces how stream data analytics empower businesses to harness real-time data for faster, smarter decision-making and enhanced competitiveness.
Explore Flink 2.0's evolution in state management, from core primitives to cloud-native architecture and next-gen incremental computation.
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.
