What technique helps with real-time data integration by decoupling data producers from consumers?

The technique that assists with real-time data integration by decoupling data producers from consumers is messaging queues. This method involves a system where data producers send messages to a queue without needing to know who will receive the data. The consumers can then independently retrieve and process these messages at their own pace.

This decoupling is crucial because it enhances flexibility and reliability in data processing. Producers can continue sending data even if consumers are temporarily unavailable, resulting in better resource utilization and improved system scalability. Additionally, messaging queues often allow for features like message persistence, ensuring that no data is lost if a consumer is down when the message is produced.

While streaming is related to real-time data processing, it typically focuses on continuous data flow rather than the decoupling aspect. Batch processing deals with processing large volumes of data at once, which isn't suitable for real-time integration. Transformation involves altering data formats or structures for compatibility, but it does not inherently address the decoupling of producers and consumers in a dynamic environment.