Implement change data capture (CDC) in your system architecture to complete the cycle of data management and processing by upgrading to the premium option: Apache Kafka Connector.

This premium feature provides asynchronous delivery of a structured queue containing data change events to any Kafka consumer you choose.

Leveraging these change events, you can dynamically respond in real-time within your external systems and tools, for instance, update a dashboard to reflect the most up-to-date information from the Big Peer.

Combing Edge and Big Data

With CDC's capabilities, you combine real-time data capture and processing at the transactional edge with the scalability and analytical power of big data.

Put differently, you stay in-the-know about all changes happening within your data. That way, you can enhance data-driven decision-making, reduce operational costs, improve efficieny and resiliency, and much more.

Each Ditto transaction produces a change data message containing the type of change, such as insert, remove, and so on, and details of the change.

For more information, see Big Peer and Kafka Connector.

Common Use Cases

Create programs that receive and process egress events.

Similar to how you use Ditto's live queries to specify the changes you're interested in, your program can define queries specifying the types of data it's interested in watching and reacting to.

For instance, imagine a point-of-sale (PoS) app with requirements such as streamlining data management across your superset of data management tooling, increasing efficiency to reduce costs and mitigate potential revenue loss, and improve customer experience by offering special incentives and promotions to your most loyal customers, as follows: