The article explores Change Data Capture (CDC), a method for tracking database changes, highlighting its advantages over traditional daily snapshots. It details three CDC implementation approaches: using database triggers (e.g., in PostgreSQL), capturing API requests and using a message broker (e.g., Kafka), and leveraging change streams within a data warehouse (e.g., Snowflake). The article compares these methods, weighing their pros and cons in terms of performance, scalability, and ease of implementation. A subsequent discussion critiques the presented methods, suggesting alternative, more robust solutions based on logical replication tools like Debezium.