Realtime Compute for Apache Flink

Realtime Compute for Apache Flink offers a highly integrated platform for real-time data processing, which
optimizes the computing of Apache Flink. With Realtime Compute, we are striving to deliver new solutions to
help you upgrade your big data capabilities in your digital transformations.

Buy Now Contact Sales Console

Overview
Features
Related Solutions
Scenarios
Pricing
Documentation

Overview

Overview
Features
Related Solutions
Scenarios
Pricing
Documentation

High-performance Platform

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.

Real Time is the Future - Apache Flink Best Practices in 2020

Download Free White Paper

{"moduleinfo":{"resId":"","bigTitle":"","subtitle":"","note":"","floor":"","benefits":"Features","outputNews4Partner":"false","outputBuyBtn4Partner":true,"cardColor":"#fff","tipColor":"#F5F5F6","iconColor":"#fff"},"regions":[],"os":[],"products":[],"news":[],"benefits":[{"icon":"https://img.alicdn.com/tfs/TB1duUo27L0gK0jSZFAXXcA9pXa-112-128.png","title":"Ultra-High Performance - Features high throughput and scalability","content":"Significantly improves the SQL in the Apache Flink community, with the throughput for a job reaching millions of data records per second and the data processing delay reduced to the second level.","alt":""},{"icon":"https://img.alicdn.com/tfs/TB1qNgNtz39YK4jSZPcXXXrUFXa-122-128.png","title":"Stable and Secure - Uses exactly-once semantics, achieves automatic fault recovery, and isolates resources","content":"Uses exactly-once semantics to ensure that no duplicate data is processed and no data goes unprocessed, runs computations based on distributed clusters to enable automatic fault recovery, and isolates compute resources between tenants to prevent negative effects on each other.","alt":""},{"icon":"https://img.alicdn.com/tfs/TB1nHJIp3gP7K4jSZFqXXamhVXa-112-120.png","title":"Easy to Use - Supports SQL, online development, and user-defined extensions (UDXs)","content":"Supports standard SQL, which helps you reduce training costs, quickly get started, and focus on your business logic; offers a fully managed online development platform that integrates development, debugging, and administration of stream processing jobs; provides a wide variety of coding assistance features, such as online debugging, intelligent code completion, and online administration."},{"icon":"https://img.alicdn.com/tfs/TB17A7h22b2gK0jSZK9XXaEgFXa-108-128.png","title":"Powerful Functions - Offers a one-stop platform for you to handle issues involving real-time and offline data processing","content":"Supports SQL to implement real-time and offline data cleansing, data analysis, data synchronization, computations over disparate data sources, and features of a data lake; allows you to perform association queries on streaming data and static data."}],"$root":{"moduleinfo":{"resId":"","bigTitle":"","subtitle":"","note":"","floor":"","benefits":"Features","outputNews4Partner":"false","outputBuyBtn4Partner":true,"cardColor":"#fff","tipColor":"#F5F5F6","iconColor":"#fff"},"regions":[],"os":[],"products":[],"news":[],"benefits":[{"icon":"https://img.alicdn.com/tfs/TB1duUo27L0gK0jSZFAXXcA9pXa-112-128.png","title":"Ultra-High Performance - Features high throughput and scalability","content":"Significantly improves the SQL in the Apache Flink community, with the throughput for a job reaching millions of data records per second and the data processing delay reduced to the second level.","alt":""},{"icon":"https://img.alicdn.com/tfs/TB1qNgNtz39YK4jSZPcXXXrUFXa-122-128.png","title":"Stable and Secure - Uses exactly-once semantics, achieves automatic fault recovery, and isolates resources","content":"Uses exactly-once semantics to ensure that no duplicate data is processed and no data goes unprocessed, runs computations based on distributed clusters to enable automatic fault recovery, and isolates compute resources between tenants to prevent negative effects on each other.","alt":""},{"icon":"https://img.alicdn.com/tfs/TB1nHJIp3gP7K4jSZFqXXamhVXa-112-120.png","title":"Easy to Use - Supports SQL, online development, and user-defined extensions (UDXs)","content":"Supports standard SQL, which helps you reduce training costs, quickly get started, and focus on your business logic; offers a fully managed online development platform that integrates development, debugging, and administration of stream processing jobs; provides a wide variety of coding assistance features, such as online debugging, intelligent code completion, and online administration."},{"icon":"https://img.alicdn.com/tfs/TB17A7h22b2gK0jSZK9XXaEgFXa-108-128.png","title":"Powerful Functions - Offers a one-stop platform for you to handle issues involving real-time and offline data processing","content":"Supports SQL to implement real-time and offline data cleansing, data analysis, data synchronization, computations over disparate data sources, and features of a data lake; allows you to perform association queries on streaming data and static data."}]},"$moduleId":"5601292470"}

Features

: Ultra-High Performance - Features high throughput and scalability
Significantly improves the SQL in the Apache Flink community, with the throughput for a job reaching millions of data records per second and the data processing delay reduced to the second level.

: Stable and Secure - Uses exactly-once semantics, achieves automatic fault recovery, and isolates resources
Uses exactly-once semantics to ensure that no duplicate data is processed and no data goes unprocessed, runs computations based on distributed clusters to enable automatic fault recovery, and isolates compute resources between tenants to prevent negative effects on each other.

: Easy to Use - Supports SQL, online development, and user-defined extensions (UDXs)
Supports standard SQL, which helps you reduce training costs, quickly get started, and focus on your business logic; offers a fully managed online development platform that integrates development, debugging, and administration of stream processing jobs; provides a wide variety of coding assistance features, such as online debugging, intelligent code completion, and online administration.

: Powerful Functions - Offers a one-stop platform for you to handle issues involving real-time and offline data processing
Supports SQL to implement real-time and offline data cleansing, data analysis, data synchronization, computations over disparate data sources, and features of a data lake; allows you to perform association queries on streaming data and static data.

Explore Solutions for Your Business

Big Data Consulting Services for Enterprise Data Technology

Help assess your big data maturity and plan big data adoption with actionable insights, speeding up your digital transformation and mapping out your digital future.

Learn More

Big Data Consulting Services for Retail

Help you assess your big data maturity and plan your big data journey in two to six weeks, transforming your retail business through big data technologies.

Learn More

Personalized Content Recommendation

Personalized Content Recommendation solution helps media companies build a discovery service for their customers to find the most appropriate content.

Learn More

Alibaba Cloud Credit Risk Management

Alibaba Cloud Credit Risk Management Solution allows you to easily apply machine learning and use your own dataset to develop, train, and deploy credit risk models.

Learn More

Scenarios

Real-time Data Analysis
Typical Architecture for Real-time Processing
IoT Solutions

Real-time Data Analysis

Batch processing models cannot meet the demand for analyzing data in real time. Realtime Compute for Apache Flink offers an end-to-end data processing platform that seamlessly integrates streaming data storage systems, such as DataHub and Log Service, for real-time analysis. Combined with components like DataV from the DTplus platform and BI reports, Realtime Compute for Apache Flink allows you to quickly build a real-time data processing platform.

Benefits

Easy Adoption
Allows you to analyze data in real time by using SQL.
Ultra-High Performance
Achieves a high throughput of over 100 million data records per second when handling the business of Alibaba Group during peak hours.
One-Stop Solution
Seamlessly integrates upstream and downstream data storage systems.

Typical Architecture for Real-time Processing

Description

Data sources continuously generate and send data to streaming data storage systems. The streaming data from these systems enters the Realtime Compute system and initiates stream processing jobs. The result data of the jobs is then sent to target data storage systems.

Benefits

Data Generation
Handle large amounts of data continuously generated from data sources.
Streaming Data Storage
Allows you to publish and subscribe to messages, and enables streaming data to enter the Realtime Compute for Apache Flink system in real time.
Real-time Processing
Offers an integrated platform for development and administration, which allows you to easily implement real-time data processing.
Data Storage
Integrates with a wide range of data storage systems, which helps you easily consume data.
Data Consumption
Instantly consumes data.

IoT Solutions

IoT Hub allows you to process big data with Realtime Compute for Apache Flink and DataHub. Realtime Compute for Apache Flink captures data from IoT sensors and runs computations over the captured data in real time. The result data of the computations is then used for monitoring, alerting, and customizing reports. You can also integrate StreamCompute with IoT Hub to consume the result data.

Benefits

Easy Adoption
Enables you to easily resolve IoT issues with SQL and user-defined functions (UDFs).
Ultra-High Performance
Achieves a high throughput of over 100 million data records per second when handling the business of Alibaba Group during peak hours.
High Scalability
Allows you to easily add devices and handle a sharp increase in data volume.

Ready to Get Started with Realtime Compute?

Explore More About Realtime Compute?

Console > Documentation >