Introduction to Change Data Capture (CDC) Practices

Change Data Capture (CDC) is a technique that continuously monitors a source database for DML changes (inserts, updates, deletes), extracts the changed rows (the "delta"), and propagates them to downstream systems such as data warehouses, analytics platforms, or other applications.

Directly querying the source for large reports can consume significant resources, cause network congestion, and introduce latency, especially when there is no low‑load window. CDC mitigates these issues by providing incremental, near‑real‑time data loads that do not affect the performance of the original system.

Modern CDC implementations typically read the database transaction log (or similar change log) to capture changes reliably. They ensure at‑least‑once delivery, preserve the order of events, and may perform schema conversion to accommodate different target data formats.

A production‑ready CDC system must guarantee ordered delivery of changes, provide delivery guarantees (e.g., at‑least‑once), and handle data format transformations so that diverse downstream systems can consume the updates correctly.

By using CDC, organizations can keep analytical and reporting environments up to date with the latest operational data, enabling timely business decisions without overloading the primary transactional databases.