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- Detect data mutation patterns with Debezium
- Debezium asynchronous engine
- Debezium and TimescaleDB
- Streamlined Performance: Debezium JDBC connector batch support
- Debezium Operator Takes off to the Clouds
- Debezium signaling and notifications - Part 3: JMX channel
- Online machine learning with the data streams from the database
- Debezium signaling and notifications - Part 2: Customisation
- Debezium signaling and notifications - Part 1
- Image classification with Debezium and TensorFlow
- Streaming Vitess at Bolt
- Distributed Data for Microservices — Event Sourcing vs. Change Data Capture
- Building Audit Logs with Change Data Capture and Stream Processing
- Streaming Cassandra at WePay - Part 1
- Reliable Microservices Data Exchange With the Outbox Pattern
- Automating Cache Invalidation With Change Data Capture
- Materializing Aggregate Views With Hibernate and Debezium
- Five Advantages of Log-Based Change Data Capture
- Creating DDD aggregates with Debezium and Kafka Streams
- Streaming Data Changes from Your Database to Elasticsearch
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Debezium Blog
Change events streamed from a database by Debezium are (in developer parlance) strongly typed. This means that event consumers should be aware of the types of data conveyed in the events. This problem of passing along message type data can be solved in multiple ways:
