The Neo4j Connector for Apache Spark now supports streaming operations, enabling bi-directional integration with popular streaming sources such as AWS Kinesis, Google Pubsub, and others. This feature allows customers to engineer data pipelines together with Graph Data Science, unlocking powerful use cases like Streaming ETL, data enrichment, trigger event detection, and machine learning. The connector reuses the Spark streaming API, creating a situation where Neo4j behaves just like any other streaming source, making it easy for developers to leverage their previous experience in batch operations. The feature is compatible with Neo4j AuraDB Free, Enterprise, Professional, as well as Neo4j Enterprise Edition and Community without limitations, supporting most modern versions of Apache Spark >= 2.4.5, including Spark 3.