Integrating databases with Apache Kafka for streaming data is a frequent topic in community discussions, and the process often involves Oracle, SQL Server, or DB2 databases. The primary methods for achieving this integration include using the JDBC connector for Kafka Connect or employing log-based Change Data Capture (CDC) tools. The JDBC connector is ideal for prototyping and low-volume tasks, allowing data to be streamed to and from any relational database that supports JDBC. In contrast, CDC tools provide a more comprehensive solution by capturing every event from a database's transaction log, making them suitable for high-fidelity, low-latency data streaming, particularly in event-driven applications. While JDBC is good for simple, low-volume tasks, CDC is recommended for applications requiring full event data capture. Both methods leverage Kafka Connect, a core component of Apache Kafka, to facilitate scalable and resilient integration between Kafka and other systems, offering flexibility in switching data sources and targets within the architecture.