Everyone who works with data has heard the term "change data capture" (CDC). The CDC is a software design approach that is based on catching incremental data changes. Within this approach real-time data of active databases replicates as analytical data sources or to read replications. It is also used to trigger events based on data changes.
Most modern databases support CDC through transaction logs, which are sequential records of all changes made in the database, while the actual data is contained in a separate file. As a result, data engineers can leverage CDC to build data pipelines that can capture and process real-time data changes with ease.
What is Debezium?
Debezium is a distributed platform created for the CDC that is well-known among data professionals, including data engineers. It uses database transaction logs to create event streams when row-level changes occur. Applications that listen for these events can perform necessary actions based on incremental data changes,
making it an important tool for data engineering workflows.
Debezium provides a library of connectors that support the various databases available today, making it easier for data engineers to integrate with different databases as part of their data engineering projects. These connectors can track and record row-level changes in database schemas, and then post changes to a streaming service like Kafka.
Typically, one or more connectors are deployed in a Kafka Connect cluster and configured to monitor databases and publish data change events to Kafka. The Kafka Connect distributed cluster provides fault tolerance and scalability, ensuring that all configured connectors always work.
Why do you need Debezium?
Debezium enables data engineers to respond almost immediately to data changes in the DBMS, including insert, update, and delete events. This includes sending push notifications to one or more mobile devices, aggregating changes, and generating a patch stream for objects. Debezium distributes monitoring processes or connectors across multiple nodes, replicating events to minimize the risk of information loss.
The principle of Debezium's work can be presented as follows:
• Debezium data source connectors send records to Apache Kafka, and by default, changes to one DBMS table are written to the Kafka topic, the name of which corresponds to the table name;
• After change event records are in Apache Kafka, various Debezium receiver connectors in the Kafka Connect ecosystem can transfer records to other databases, datastores, analytics systems, or caches.
• The Debezium server is configured to use one of the original Debezium connectors to collect changes from the original database.
Debezium is one of the most famous open-source CDC systems and can be one of the components of the data system. It is a full-fledged and rapidly evolving CDC system that can replace existing proprietary change capture systems. The system is based on the Kafka product stack and is implemented in Java, making it an easy-to-use tool for data engineers who are familiar with Java programming.