Featured Posts
- 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
In this post, we are going to talk about a CDC-CQRS pipeline between a normalized relational database, MySQL, as the command database and a de-normalized NoSQL database, MongoDB, as the query database resulting in the creation of DDD Aggregates via Debezium & Kafka-Streams.
