Stream Compute Service
- Releases Notes and Announcements
- Getting Started
- Operation Guide
- Managing Jobs
- Developing Jobs
- Monitoring Jobs
- Events and Diagnosis
- Managing Metadata
- Tuning Jobs
- Managing Clusters
- Managing Permissions
- SQL Developer Guide
- DDL Statements
- Connectors
- SET Statement
- Operators and Built-in Functions
- Identifiers and Reserved Words
- ETL Developer Guide
Use Cases
Last updated: 2023-11-07 15:27:51
Stream Compute Service applies to the following scenarios:
Real-time extract, transform, and load (ETL) between heterogeneous data services
Real-time recommendation, real-time risk control, and database query acceleration
Real-time data warehouses, dashboards, and reports
Real-time monitoring, exception detection, and alerting
Real-time ETL
ETL is the process of loading data from a business system to the data sink after extraction, cleansing, and transformation. It aims to consolidate the scattered data complying with different standards in an enterprise to facilitate the decision-making of the enterprise.
Real-time financial risk management
Fast detection of financial risks can effectively reduce losses. By combining financial transaction big data with Stream Compute Service and introducing feature model algorithms, you can timely filter out abnormal transaction behaviors such as unauthorized transaction and implement comprehensive risk management to improve financial security.
IoT monitoring
Early detection of potential faults during the operations of industrial devices can greatly reduce production risks. Stream Compute Service can collect, aggregate, analyze, and filter device sensor data to implement monitoring and alerting for device exceptions in seconds, ensuring smooth operations of industrial production.
Targeted ecommerce recommendations
In ecommerce transactions, Stream Compute Service can extract feature variables in real time and promptly track users' desired categories to predict their consumption trends and provide basic capabilities for targeted recommendations. This helps enhance the shopping experience and drive purchases.
Database query acceleration
Relational databases face the challenges of weak performance and poor scalability in the case of massive data. Stream Compute Service can synchronize data from relational databases to ES in real time. ES provides capabilities of high concurrency and low latency query, SQL, and elastic scaling for massive data, meeting the demand for database query acceleration.
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