Change data capture (CDC) to Kafka

Change Data Capture (CDC) is a technique that identifies and records every change in a database, capturing modifications as discrete events to keep systems synchronized in near real-time. Unlike traditional batch processes, CDC continuously monitors databases, reducing system load and latency by capturing only changes rather than entire datasets. Integrating CDC with Apache Kafka enhances this process, offering a reliable, scalable pipeline for distributing change events to downstream systems. Kafka's architecture, with features such as partitioning and replication, ensures high-throughput, fault-tolerant delivery of events, making it a suitable choice for enterprises dealing with fast data. Implementing a CDC-to-Kafka pipeline often involves tools like Kafka Connect and Debezium, which streamline the integration and ensure efficient change capture. This architecture supports various use cases, including real-time analytics, data synchronization across systems, and event-driven microservices, enabling organizations to maintain data consistency, reduce latency, and enhance scalability and fault tolerance. By decoupling data sources from consumers, the CDC and Kafka combination allows enterprises to build responsive systems that react to data changes swiftly without overwhelming primary databases.