Realtime Compute

Realtime Compute 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.

Realtime Compute 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, you can process and analyze big data in real time for business insights and decision making.

Benefits

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.
Stable and Advanced
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.
Cutting-Edge Technology
Resolves a wide range of issues that involve Flink, with the expertise of Apache Flink committers.

Features

Ultra-High Performance

Features high throughput and scalability.

Ultra-High Efficiency

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.

Stable and Secure

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).

Easy to Use

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.

Powerful Functions

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.

Scenarios

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

Real-time Data Analysis

Real-time Data Analysis

Batch processing models cannot meet the demand for analyzing data in real time. Realtime Compute 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 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

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 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 Solutions

IoT Solutions

IoT Hub allows you to process big data with Realtime Compute and DataHub. Realtime Compute 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.