Change data capture (CDC) is a process that monitors and replicates changes such as inserts, updates, and deletes in real-time or near-real-time across databases and downstream systems. It is especially beneficial for synchronizing multiple databases, enhancing cache or search index performance, real-time logging, and implementing event-driven architectures like command query responsibility segregation (CQRS). The text details a tutorial on establishing a real-time CDC pipeline using Postgres, Google Cloud Storage, Redpanda, and Debezium. The process involves setting up a Postgres instance with logical replication, configuring a Debezium connector to monitor database changes, and creating a Kafka Connect container to link Postgres and Redpanda. Additionally, a Google Cloud Storage (GCS) connector is created to store the data from Redpanda into a GCS bucket, ensuring efficient data movement and storage. The tutorial provides step-by-step guidance on setting up the necessary software and configurations, showcasing how CDC can reliably maintain synchronized data across different systems and use cases.