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Apache flink

AI Trends Reshaping Data Engineering in 2026

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 vs. Apache Paimon: Two Engines for the Real-Time Lakehouse

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.

The Delta Join in Apache Flink: Architectural Decoupling for Hyper-Scale Stream Processing

Discover how Delta Join in Apache Flink revolutionizes stream processing, reducing state and costs while boosting performance and stability.

Introducing Fluss: Streaming Storage for Real-Time Analytics

Today, we are excited to introduce Fluss, a cutting-edge streaming storage system designed to power real-time analytics.

Apache Flink FLIP-15: Smart Stream Iterations & Optimization

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.

Realtime Compute for Apache Flink Unveils Incremental Processing & Streaming

From the 2025 Apsara Conference: Alibaba Cloud debuts major Realtime Compute for Apache Flink upgrades in computing, storage, and real-time AI integration.

Real-Time Lakehouse Solutions: Apache Flink & Apache Paimon Integration

Alibaba Cloud presents key optimizations in Flink-Paimon real-time lakehouse architecture, including the Variant data type for efficient semi-structur...

Alibaba Cloud, Ververica, Confluent, and LinkedIn Join Forces on Streaming Innovation for Agentic AI

Apache Flink Agents: A landmark collaboration to build a scalable, production-grade framework for event-driven streaming agents powered by Apache Flink.

Apache Flink FLIP-18: Accelerating Sorting with Code Generation

FLIP-18: Boost Flink's sorting efficiency with code generation, optimizing memory access and byte order handling.

Apache Flink FLIP-17: Side Inputs for Stream Processing API

FLIP-17 introduces side inputs to Apache Flink's DataStream API for more flexible and efficient stream processing with auxiliary data.

FLIP-16: Reliable Iterative Stream Processing in Apache Flink

FLIP-16 explores and addresses the challenges of reliable iterative stream processing in Flink, highlighting memory, complexity, and performance issue.

Building a Unified Lakehouse for Large-Scale Recommendation Systems with Apache Paimon at TikTok

TikTok transitioned to a unified Lakehouse architecture, powered by Apache Paimon, to optimize large-scale recommendation models (LRMs) that utilize user behavior sequences.

The Rise of Stream Data Analytics: Why Real-Time Insights Are the New Competitive Edge

This article introduces how stream data analytics empower businesses to harness real-time data for faster, smarter decision-making and enhanced competitiveness.

Flink State Management: A Journey from Core Primitives to Next-Generation Incremental Computation

Explore Flink 2.0's evolution in state management, from core primitives to cloud-native architecture and next-gen incremental computation.

Accelerate Data Ingestion in Real-time Lakehouse with Apache Flink CDC

Learn how Apache Flink CDC accelerates real-time data ingestion in modern lakehouse architectures, enabling seamless and efficient data processing.

Apache Paimon: Real-Time Lake Storage with Iceberg Compatibility 2025

Discover Apache Paimon: real-time lake storage with Iceberg compatibility, optimized for streaming and multimodal AI applications.

Flink Agents: An Event-Driven AI Agent Framework Based on Apache Flink

Flink Agents: An event-driven AI framework on Apache Flink for real-time, scalable, and autonomous AI applications.

From Data Streams to Actionable Insights: Grab's Journey with Apache Flink in Real-Time Analytics and Data Quality

Discover how Grab leverages Apache Flink for real-time analytics and data quality, transforming raw data into actionable insights.

Apache Flink FLIP-13: Side Outputs for Multi-Stream Processing

Master Apache Flink FLIP-13 side outputs for flexible data processing. Handle corrupted data, late arrivals, and multi-stream routing with OutputTag and CollectorWrapper patterns.

Apache Flink FLIP-14: CrossGroup Operator for Graph Processing

Discover Apache Flink FLIP-14 CrossGroup operator for efficient data pairing and graph analysis. Optimize memory usage, reduce Cartesian products, and enhance social network processing.