DZone

In the scenarios of relational network analysis, relationship modeling, and real-time recommendation, using graph databases for background data is becoming popular, and some scenarios, such as recommendation systems and search engines, require high real-time graph data. To improve the real-time performance of data, stream processing is widely used for incremental processing of updated data in real-time. To support the stream processing of graph data, the Nebula Graph team developed Nebula Flink Connecter to empower Flink to operate stream processing of data in Nebula Graph.

Flink is a new generation of computing engines that can support both stream and batch processing of data. It reads data from a third-party storage engine, processes them, and then writes them to another storage engine. A Flink Connector works like a connector, connecting the Flink computing engine to an external storage system.

Source: DZone