Using Graph Processing for Kafka Streams Visualizations

The text discusses the integration of graph capabilities into event streaming applications using Apache Kafka® and Neo4j, a native graph database. It explains that graphs are useful when relationships between items dominate an application, such as in social networks or financial fraud detection. By adding graph abilities to stream processing engines like ksqlDB, developers can more easily approach their use cases. The text provides a step-by-step guide on how to turn streams into graphs with Neo4j and the Neo4j-Streams plugin, including enriching and visualizing data, using powerful graph algorithms, and sending results back to Kafka. It also highlights the benefits of using Confluent Cloud for managing event streaming services without worrying about extra infrastructure management.