Cloud Stream Service
Cloud Stream Service (CS) is a real-time big data stream analysis service running on the Huawei cloud. Computing clusters are fully managed by CS, enabling you to focus on Stream SQL services. CS is compatible with Flink APIs, and CS jobs run in real time, making cloud data easy to calculate and analyze.
Join the open beta test to claim a limited free trial. Learn more
Enterprise users could join the open beta freely.
Ease of Use
StreamSQL can be used to define data inflow, data processing, and data outflow. Service logics can be implemented quickly, facilitating stream data analysis.
CS provides visualized information on running jobs.
Pricing is calculated based on units of SPUs. You are charged based on the running duration (with second-level accuracy) of the SPUs specified by you.
High Throughput and Low Latency
The Flink and Dataflow models are used to achieve a complete real-time calculation framework.
Features ease of use, low latency, and high throughput. Stream analysis can be conducted using Stream SQL and user-defined jobs.
Online Stream SQL editing is supported and abundant SQL functions are provided to meet complex service requirements.
Computing clusters are fully managed without raising user awareness, enabling you to focus on stream analysis.
SPU resources specified during job creation are charged by duration, counted by second.
IoT devices or customer edge (CE) devices upload streaming data to Data Ingestion Server (DIS) or other cloud storage services. Cloud Stream Service reads data directly in DIS, performs data analysis (including fault detection, data cleansing, statistical analysis, and indicator warning), and makes the analysis results persistent or pushes alarm notifications in real time.
Common IoT functions such as area, yaw, and distance detection functions are provided.
The Apache Flink execution engine serves as a complete real-time computing framework.
Tenants are isolated from each other, ensuring data security.
Aggregate functions such as Window and Join are supported. SQL is used to express service logics, enabling quick and easy service implementation.
CS reads data from the DIS, and supports natural backpressure and high-throughput pressure. Millisecond-level latency meets the requirements of real-time calculation scenarios.
Triple security protection mechanisms for tenants ensure operation security.
Large-scale cluster computing and auto scaling of clusters significantly reduce cost.