Neo4j Announces Availability of Neo4j Streams for Real-Time Correlations on Apache Kafka


Neo4j Streams Connector for Kafka and Confluent Platform Enables Real-Time Connected Data Insights on Event Streams

Kafka Summit, SAN FRANCISCO, Calif. – October 1, 2019 – Neo4j, the leader in graph databases, announced that Neo4j now integrates with Apache Kafka® and Confluent® Platform to connect Kafka event streams. Neo4j Streams™ is available as a Neo4j Server Extension to all Neo4j and Kafka users.

When event streams are enriched with powerful graph-based analytics, clear correlations can be made in real time to enable organizations to flex and innovate at the frenetic pace of business today.

[Caption: Neo4j works with Kafka and Confluent to enrich event streams with powerful graph-based analytics.]

Kafka is a distributed event streaming platform capable of handling trillions of events a day. Neo4j, Kafka and Confluent customers will now have seamless, supported integration with the new connector. Customers can use Neo4j Streams for a variety of real-time use cases including financial fraud analysis, knowledge graphs and customer 360.

Neo4j’s SVP of Business and Corporate Development, Fawad Zakariya is tasked with expanding the most comprehensive graph database ecosystem. He explained why Neo4j Streams is important for real-time enterprise applications.

“We’ve integrated the world’s most powerful graph database with the most popular streaming platform, fully supported for Confluent and Neo4j enterprise customers,” said Zakariya. “As enterprises demand near real-time capabilities to fight fraud, respond to customer behavior and react to business events, this integration unlocks new ways for them to innovate by combining the power of connected context with real-time streaming data.”

Simon Hayes, Vice President of Corporate and Business Development at Confluent, discussed how Neo4j Streams, the Neo4j server extension for Kafka, benefits Neo4j and Confluent customers.

“Data is only as valuable as how quickly someone can take action on it, the millisecond it was created,” said Hayes. “That’s why 60 percent of Fortune 100 companies have put an event streaming platform at the heart of their businesses. Through this integration with Neo4j Streams, customers can more quickly and easily see the relationship between events and turn that data into context so it can be acted upon faster.”

Neo4j Streams in Depth

The Neo4j integration with Kafka and Confluent Platform makes change events from Neo4j available in Kafka. Other applications can update downstream systems or add procedures that can be used to send and receive data from Kafka for accessing transaction events. Additionally, Neo4j users can consume events from Kafka and turn these events into graph structures, like change data capture (CDC) or data sink to ingest any kind of Kafka event into a graph.

The Neo4j sink connector, a component of Neo4j Streams, has earned the Verified Gold level by Confluent as part of the Confluent Verified Integrations Program. This distinction assures connectors meet technical and functional requirements of the Kafka Connect API, an open source component of Kafka which provides the framework for connecting Kafka with external systems such as databases. By adhering to the Kafka Connect API, customers can expect a better user experience, scalability, and integration with Confluent Platform, including Schema Registry and Control Center, as well as Confluent Cloud, the fully managed cloud-native streaming service from Confluent based on Kafka.

For More Information

Neo4j Streams, the Neo4j Server Extension for Kafka is available to all Neo4j Enterprise Edition and Confluent customers. Comprehensive support is included for Neo4j Enterprise Edition customers. More information can be found at:

Neo4j is a sponsor of Kafka Summit in San Francisco September 30-October 1, and will be presenting a session titled Extending the Stream/Table Duality into a Trinity, with Graphs.


About Neo4j

Neo4j is the leading graph database platform that drives innovation and competitive advantage at Airbus, Comcast, eBay, NASA, UBS, Walmart and more. Thousands of community deployments and more than 300 customers harness connected data with Neo4j to reveal how people, processes, locations and systems are interrelated. Using this relationships-first approach, applications built using Neo4j tackle connected data challenges including artificial intelligence, fraud detection, real-time recommendations and master data. Find out more at

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© 2019 Neo4j, Inc., Neo Technology®, Neo4j®, Cypher® and Neo4j® Bloom™ are registered trademarks or a trademark of Neo4j, Inc.

Apache, Apache Kafka, Kafka, and associated open source project names are trademarks of the Apache and Software Foundation and CONFLUENT is a registered trademark of Confluent, Inc. All other marks are owned by their respective companies.