Glossary · Database

Change Data Capture (CDC)

Change data capture (CDC) is a technique for detecting and streaming every insert, update, and delete in a database as it happens, so other systems can react to changes in real time.

CDC taps the database's transaction log–the internal record of every change–and turns it into an event stream: "row 4182 in orders changed status from pending to shipped at 14:03". Tools like Debezium use this to sync warehouses, refresh caches, and trigger downstream processes within seconds of a change, without repeatedly polling tables. CDC matters because batch syncs leave you acting on yesterday's data; CDC closes the gap to near zero. The trade-off is operational complexity–log-based CDC requires infrastructure and database configuration that many teams only need for their most time-sensitive flows.

In practice

How AI for Database applies it

AI for Database gives you CDC-style outcomes without the infrastructure: define a condition in plain English and a workflow watches your database and fires Slack, email, or webhook actions when it changes.
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