Flink (VVR) is a commercial version developed based on Apache Flink (referred to as Flink in this topic). Ververica Runtime (VVR) is fully compatible with Flink and provides high value-added features such as GeminiStateBackend to improve job performance and stability.
Background information
The core of Flink is a streaming execution engine. The engine provides features such as data distribution, data communication, and fault tolerance for distributed streaming computing. Based on the streaming execution engine, Flink provides APIs of a higher abstraction level to allow you to compile distributed jobs.
Flink (VVR) is fully compatible with Flink. For more information, see the following documentation:
Scenarios
Flink is widely used for real-time big data computing. This section describes the scenarios of Flink from the perspectives of technologies and enterprise applications.
Technologies
From the perspective of technologies, Flink is suitable for the following scenarios:
Real-time extract, transform, and load (ETL) and data streams
Data is delivered from Point A to Point B by using the real-time ETL process and data streams. During data delivery, data cleansing and integration may be required, such as real-time indexing in the search system and the ETL process in real-time data warehousing.
Real-time data analysis
Real-time data analysis is a process of extracting and integrating required information from raw data to achieve your business objectives. For example, you can view the top 10 products sold per day, the average turn-around time in the warehouse, the average document click rate, and the open rate for push notifications. Real-time data analysis allows you to view real-time reports or dashboards.
Event-driven applications
An event-driven application is a system that processes or reacts to subscription events. Event-driven applications depend on internal states and respond to suspicious events detected during fraud detection or in the risk control system or O&M exception detection system. When your behavior triggers a risk control point, the system captures the event and analyzes the current and previous behavior to determine whether to perform risk control over your behavior.
Enterprise applications
From the perspective of enterprise applications, Flink is suitable for the following scenarios:
Business department: real-time risk control, real-time recommendation, and real-time indexing of search engines
Data department: real-time data warehousing, real-time reports, and real-time dashboards
O&M department: real-time monitoring, real-time exception detection and alerting, and end-to-end debugging