Debezium Connectors

Each database type has a special connector.

• MySQL Connector
• PostgreSQL Connector
• MongoDB Connector
• SQL Server Connector

The connector’s job is to read the transaction log and turn changes into events.

Kafka Connect

Debezium runs as a set of Kafka Connect plugins. Kafka Connect provides the runtime where connectors operate. It handles tasks like scaling, error recovery, and message delivery.

Apache Kafka

Kafka is the data pipeline backbone. Events from Debezium are written into Kafka topics.

• Each table usually has its own topic.
• Kafka ensures the events are delivered reliably and can be read by many consumers.

Consumers

Consumers are systems or apps that subscribe to Kafka topics. They can:

• Process streams in real time (with tools like Flink or Kafka Streams).
• Update a search engine like Elasticsearch.
• Sync data into a data warehouse (Snowflake, BigQuery, Redshift).
• Trigger actions in microservices (e.g., send an email when an order is created).
• Update a cache like Redis.

Monitoring and Management

Debezium provides metrics through JMX. These metrics can be collected by Prometheus and displayed with Grafana. This helps teams monitor whether Debezium is healthy and running well.

Event Format

Each change captured by Debezium is turned into an event message. An event usually contains:

• The before state (data before the change).
• The after state (data after the change).
• Metadata (operation type: insert, update, delete, and timestamp).

This makes it easy for consumers to know what happened and how to react.

Why This Architecture Matters

The Debezium architecture offers key benefits:

• Real-time data flow – no waiting for batch jobs.
• Scalable – many consumers can read the same events without slowing down the source database.
• Reliable – by reading directly from logs, no change is missed.
• Flexible – supports many different sinks (search, analytics, microservices).

Conclusion

Debezium’s architecture is built to make Change Data Capture simple and reliable. By combining database connectors, Kafka, and consumers, it creates a strong data pipeline.

In short:

• Databases keep business data.
• Debezium connectors capture changes from logs.
• Kafka transports the events safely.
• Consumers use the events for analytics, search, sync, and more.

This architecture makes Debezium a powerful tool for building real-time, event-driven systems.