Featured Posts

Tags
apache kafka apache kafka apicurio avro aws batch caassandra camel cassandra cdc channels community community stories connectors containers cqrs custom datalake db2 ddd debezium debezium server debezium ui deduplication discussion docker elasticsearch event sourcing exactly once semantics example examples features fedora flink hiring ibmi iceberg informix integration introduction jaeger jdbc json kafka kafka streams kafka streams kogito ksql kubernetes lakehouse machine learning mariadb microservices mongo mongodb mysql news newsletter notifications online learning operator oracle outbox performance postgres presentation production quarkus questdb rds releases schema scylla secrets sentry serialization signaling smt snapshots spanner spark sql sqlserver tensorflow testcontainers tests time series timescaledb topics tracing transactions vagrant vitess website

Debezium Blog

One of the typical Debezium uses cases is to use change data capture to integrate a legacy system with other systems in the organization. There are multiple ways how to achieve this goal

  • Write data to Kafka using Debezium and follow with a combination of Kafka Streams pipelines and Kafka Connect connectors to deliver the changes to other systems

  • Use Debezium Embedded engine in a Java standalone application and write the integration code using plain Java; that’s often used to send change events to alternative messaging infrastructure such as Amazon Kinesis, Google Pub/Sub etc.

  • Use an existing integration framework or service bus to express the pipeline logic

This article is focusing on the third option - a dedicated integration framework.

Read More