What’s New?

Neo4j Connector for Kafka 5.1 introduces several improvements and some breaking changes over the previous minor version.

Configuration

  • Settings for both Source and Sink connectors have been reviewed and most of the settings have been renamed to follow a consistent naming structure. Refer to Source Configuration Settings and Sink Configuration Settings for an exhaustive list of supported configuration settings and their naming scheme.

  • Settings which represents duration values, such as connection timeouts, retry timeouts, polling intervals, etc. now accepts more human friendly values, such as 5s, 1m, etc. Refer to Source Configuration Settings and Sink Configuration Settings for detailed formatting rules for these settings.

  • Settings which accepts multiple values now use , as the common delimiter.

  • Settings are re-implemented to adhere to Kafka configuration practices, and performs more user-friendly in UI supported environments, such as Confluent Control Center.

Source

  • Source connector generates messages using Kafka Connect data model and supports schema based converters such as Avro, JSON Schema and Protobuf out of the box. It is no longer possible to turn off this behavior in the connector itself, and if schema is not desired it should be handled through converters.

  • Change Data Capture is now fully supported in Source connector and should be the preferred Source connector strategy where possible.

  • User provided cursors for change tracking is now possible by setting neo4j.start-from to USER_PROVIDED and neo4j.start-from.value to a desired cursor, such as a custom change identifier from CDC.

  • It is now possible to ignore stored offsets by setting neo4j.ignore-stored-offset to true if required.

Sink

  • Changes are now applied in the order they are received from Kafka Connect, grouped by their topics.

  • Error handling is re-implemented to provide full integration with Kafka Connect infrastructure, and failing messages can be identified and forwarded to Dead Letter Queues (if configured) independently.

  • Both Change Data Capture and previous streams plugin generated change event messages are supported in CDC strategies.

  • All message fields, including message timestamp as stored in Kafka, message headers, key and value can be referenced in Cypher strategy.

  • All message fields, including message timestamp as stored in Kafka, message headers, key and value can be referenced in Pattern strategies.

  • It is now possible to name properties on nodes or relationships while defining patterns in Pattern strategies.