Using CDC to Kafka for Real-Time Data Integration

When an Apache Kafka environment needs continuous and real-time data ingestion from enterprise databases, more and more companies are turning to change data capture (CDC). Here are the top reasons why CDC to Kafka works better than alternative methods:

  • Kafka is designed for event-driven processing and delivering streaming data to applications. CDC turns databases into a streaming data source where each new transaction is delivered to Kafka in real time, rather than grouping them in batches and introducing latency for the Kafka consumers.
  • CDC to Kafka minimizes the impact on source systems when done non-intrusively by reading the database redo or transaction logs. Log-based CDC to Kafka avoids performance degradation or modification for your production sources.
  • When you move only the change data continuously, versus moving large sets of data in batches, you utilize your network bandwidth more efficiently.
  • When you move change data continuously, versus using database snapshots, you get more granular data about what occurred between the times snapshots were taken. Granular data flow allows more accurate and richer intelligence from downstream analytics systems.

Download this white paper to learn how to leverage CDC to Kafka so you can ingest real-time data without impacting your source databases. (No registration required)