Which data integration pattern is commonly used to enable real-time data exchange in CDX?

Which data integration pattern is commonly used to enable real-time data exchange in CDX?

• A. Pub/sub streaming
• B. Batch ETL with nightly runs
• C. Periodic archiving
• D. FTP file transfer

Answer: (A)

Real-time data exchange relies on event-driven messaging that decouples producers from consumers, so updates flow immediately without waiting for scheduled runs. Pub/sub streaming fits this perfectly: creators publish events to a topic, and any number of subscribers receive those events as soon as they’re produced. This setup delivers low latency, scales horizontally, and allows the same event to be consumed by multiple downstream systems, which is essential for keeping CDX data synchronized in real time. It also supports features like fan-out, durability, and the possibility to replay events if needed. Batch ETL with nightly runs, periodic archiving, and FTP file transfers all introduce delays or rely on manual, file-based transfer. They don’t provide the continuous, event-driven flow that real-time exchange requires.

Real-time data exchange relies on event-driven messaging that decouples producers from consumers, so updates flow immediately without waiting for scheduled runs. Pub/sub streaming fits this perfectly: creators publish events to a topic, and any number of subscribers receive those events as soon as they’re produced. This setup delivers low latency, scales horizontally, and allows the same event to be consumed by multiple downstream systems, which is essential for keeping CDX data synchronized in real time. It also supports features like fan-out, durability, and the possibility to replay events if needed.

Batch ETL with nightly runs, periodic archiving, and FTP file transfers all introduce delays or rely on manual, file-based transfer. They don’t provide the continuous, event-driven flow that real-time exchange requires.