Latest Buzz
Materialized tables to streamline batch and streaming data pipelines
Learn more >The Past, Present, and Future of Apache Flink
Read Blog >Recording for Flink Forward Asia Jakarta 2024
Watch Recordings >Connect your databases with Flink CDC
Learn more >Apache Paimon: Streaming Lakehouse is Coming
Read the blog >Flink CDC 3.0| A Next-generation Real-time Data Integration Framework
Read the blog >High-performance Platform For Realtime Integration, Compute, and Storage
Realtime Compute for Apache Flink offers a one-stop, high-performance platform that enables real-time big data processing based on Apache Flink. It is widely used in diverse scenarios, such as streaming data processing, offline data processing, and data lake computing. With Realtime Compute for Apache Flink, you can process and analyze big data in real time for business insights and decision making.
It's the only product around the world that provides key computing services for Alibaba Group to process large amounts of data during the Tmall Double Eleven Global Shopping Festival.
Support for Batch Processing and Stream Processing
Uses the same engine and APIs for batch processing and stream processing, which simplifies development.
Ultra-High Performance
Ten times higher than open-source Apache Flink, and five to ten times higher than Apache Spark for some performance metrics.
Cutting-Edge Technology
Resolves a wide range of issues that involve Flink, with the expertise of Apache Flink committers.
Features
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Real-Time Processing with Stream-Batch Integration
Blends real-time stream processing and batch processing, so you can clean, analyze, and sync your data effortlessly with SQL and manage data management with ease.
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Ultra-High Performance: Features High Throughput and Scalability
Improves Flink SQL in the Apache Flink community, with the throughput for a job up to millions of data records per second and the data processing delay down to seconds.
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Stable and Secure: Uses Exactly-once Semantics, Achieves Automatic Fault Recovery, and Isolates Resources
Ensures no duplicate data is processed and no data goes unprocessed with exactly-once semantics, enables automatic fault recovery based on distributed clusters, and secures data and operations by isolating compute resources between tenants.
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Streamlined Efficiency: Our Serverless, Fully Managed Service
Unlocks peak performance with a serverless architecture designed for efficient, high-scale stream processing, and provides high elasticity so you can scale your business flexibly to meet complex demands.
Use Cases
Real-time Data Warehousing
Elevate your business with a digital operational system that tracks key metrics in real-time, providing a visual snapshot of your production and operations. Make informed decisions with instant access to real-time data insights.
Real-time ETL
Seamlessly integrate data from various sources using our fully managed service, empowering your enterprise to build a robust data foundation effortlessly.
Real-time Risk Management
Safeguard your business from fraud and risks with real-time detection capabilities. Our solution helps you identify anomalies and mitigate potential losses, ensuring peace of mind for your operations.
Real-time Monitoring
Simplify your monitoring processes with efficient state management and advanced alert configurations. Stay ahead of issues and reduce maintenance costs with our comprehensive monitoring platform.
Real-time Recommendations
Delight your users with personalized recommendations based on real-time analysis of their behavior. Boost engagement and retention with tailored content and offerings.
Real-time IoT Insights
Harness the power of real-time data analysis to optimize IoT device performance and predict outcomes. Stay proactive with instant alerts and predictive maintenance, maximizing efficiency and productivity.
Product Updates
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2024-12-20 New FeaturesMaterialized tables
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2024-9-11 New FeaturesIntegration with Data Lake Formation (DLF) 2.0
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2024-7-22 New FeaturesVerverica Runtime (VVR) 8.0.8 release
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2024-5-29 Experience EnhancementsEnhanced MySQL connector
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2024-5-29 New FeaturesVerverica Runtime (VVR) 8.0.7 release
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2024-5-29 New FeaturesOperator-level state TTL
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2024-5-29 Experience EnhancementsOptimized permission management
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2024-5-29 Experience EnhancementsOptimized state compatibility check for SQL deployments
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2024-5-6 New FeaturesGUI-based creation of Simple Log Service and StarRocks catalogs
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2024-1-4 Experience EnhancementsEnhanced Hologres connector
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2024-1-4 Experience EnhancementsMySQL CDC enhancements
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2024-1-4 Experience EnhancementsEnhanced MongoDB connector
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2024-1-4 New FeaturesMongoDB catalogs
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2023-12-7 New FeaturesRealtime Compute for Apache Flink supports queue management
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2023-12-7 New FeaturesSupport for CALL, DDL, DQL, and DML statements in scripts
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2023-11-27 Experience EnhancementsEnhanced MySQL catalogs
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2023-10-23 New FeaturesData lineage of Flink SQL deployments
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2023-10-23 New FeaturesMultiple logon methods
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2023-10-23 New FeaturesOptimized automatic tuning
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2023-10-23 New FeaturesDynamic parameter configuration and resource scaling
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2023-10-23 Experience EnhancementsDATE columns as partition keys in Hologres result tables
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2023-10-23 Experience EnhancementsEnhanced MaxCompute connector
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2023-10-23 Experience EnhancementsEnhanced StarRocks connector
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2023-10-23 Experience EnhancementsEnhanced ApsaraMQ for RocketMQ connector
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2023-10-23 Experience EnhancementsEnhanced MySQL catalogs
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