Build Predictive Machine Learning with Flink | Workshop on Dec 18 | Register Now
Businesses today rely on data that is connected and event driven. Neo4j’s connected data technology allows data to be represented as a graph. Combined with the event streaming platform from Confluent enables real time data relationships; resulting in powerful, new capabilities for enterprise customers. Integration with Kafka and Confluent Platform allows change events from Neo4j to be available to Kafka, so that other systems can consume them and, for example, update downstream systems. Additionally, the integration enables Neo4j users to consume events from Kafka and turn events into graph structures.
Use flexible “whiteboard friendly” graph data modeling to understand the relationships between items in a flow of data transactions
For example, assign a fraud score to a financial transaction; or provide an influence metric with a social connection
The combination of streaming data and the leading native graph database unlock new solutions to difficult problems
Uncover fraud rings and other scams in real time with Neo4j data relationships graph database and Confluent event streaming
Neo4j and Confluent Integration