Nowadays real-time Messaging Systems has become widely used, covering a variety of use-cases, from log aggregation to real-time Stream Processing (in combination with Big Data Processing Frameworks).
In this talk we'll introduce how to use Apache Kafka (the most used Message Brocker) in combination with Neo4j through the Neo4j-Streams project, demonstrating via simple use-cases how you can leverage the information driven by the Change Data Capture Module and how to add Neo4j in your streaming flow by using the Sink module.
Nowadays real-time Messaging Systems has become widely used, covering a variety of use-cases, from log aggregation to real-time Stream Processing (in combination with Big Data Processing Frameworks).
In this talk we'll introduce how to use Apache Kafka (the most used Message Brocker) in combination with Neo4j through the Neo4j-Streams project, demonstrating via simple use-cases how you can leverage the information driven by the Change Data Capture Module and how to add Neo4j in your streaming flow by using the Sink module.