Change Data Capture from Oracle to Kafka
Move Real-Time Data from Oracle to Kafka
For streaming data from Oracle to Kafka, log-based change data capture (CDC) methodology brings several advantages over traditional bulk data extract, transform, load (ETL) solutions and in-house solutions with custom-scripts. Striim’s enterprise-grade streaming integration platform performs real-time CDC non-intrusively and with exactly once processing guarantees. Here are the top reasons for you to consider the CDC method for Oracle to Apache Kafka integration:
- Change data capture turns Oracle database operations (inserts, deletes, updates) into an event stream for Kafka Consumers. Given that Kafka is designed for event-driven processing, streaming Oracle database events in real time to Kafka — versus doing bulk data extract — helps with getting more value from Kafka and downstream consumers that use low-latency data.
- Log-based CDC from Oracle to Kafka minimizes the impact on source systems and is non-intrusive because it reads the database redo logs. It avoids performance degradation or modification for your production Oracle databases while streaming real-time data to Kafka.
- 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 from Oracle to Kafka, 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 non-intrusively move real-time data from Oracle to Kafka. (No registration required)