Using Change Data Capture to Scale Streaming Projects - RTInsights

Using Change Data Capture to Scale Streaming Projects - RTInsights

Using Change Data Capture to Scale Streaming Projects. CDC captures row-level changes to database tables and passes corresponding change events to a data streaming bus. Applications can read these change event streams and access the change events in the order in which they occurred. Change data capture minimizes resources required for processes because it only deals with data changes.

CDC minimizes the resources required for processes because it only deals with data changes. Such capabilities allow streaming projects to scale more easily.

A perfect storm of industry changes is making change data capture (CDC) all the more important in applications that use events-based and streaming data. The reason: Modern applications need a way to manage data changes and events that trigger an action downstream. Quite often, each change is used by different applications, for different purposes, at different times.

Change data capture is a system that monitors and captures the changes in data so that other software can respond to those changes. CDC captures row-level changes to database tables and passes corresponding change events to a data streaming bus. Applications can read these change event streams and access the change events in the order in which they occurred.

 A typical CDC pipeline would start with an event producer application. An example might be a shopping app where a user creates or updates an account. The app makes those changes in a database. CDC would then make the changes available to a stream engine. CDC minimizes the resources required for processes because it only deals with data changes. Such capabilities allow streaming projects to scale more easily.

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