Change data capture (CDC) is a data integration technique that continuously tracks and captures changes in a database, allowing systems to update in near real-time without the need for full data transfers. This method supports real-time analytics by ensuring multiple systems remain synchronized, facilitating data migration, and enabling event-driven microservices. It addresses limitations of traditional batch ETL processes, reducing downtime and ensuring data consistency. There are various CDC methods, including log-based, trigger-based, and timestamp-based approaches, each with its own trade-offs in terms of overhead and complexity. Log-based CDC is preferred for high-throughput environments due to its minimal impact on source databases. While powerful, CDC implementation requires careful consideration of data consistency, performance overhead, and fault tolerance, often involving complex maintenance and monitoring. Its applications span from real-time analytics and cloud migrations to microservices integration, highlighting its role as a crucial component in modern data architectures. Aerospike's platform exemplifies CDC's utility by integrating CDC through its Cross Datacenter Replication feature, ensuring real-time data distribution and synchronization.