Which technology aids in real-time event-driven architectures in Google Cloud?

The correct choice for aiding real-time event-driven architectures in Google Cloud is Dataflow. Dataflow is a fully managed stream and batch processing service that allows for real-time data processing using Apache Beam. This technology excels in processing large streams of data in real time, enabling applications to respond to events instantly as they occur.

Leveraging its capabilities, Dataflow can handle real-time ingestion of events, applying transformations, and delivering processed data to various targets, which is critical in event-driven architectures. It integrates seamlessly with other Google Cloud services, making it an ideal choice for applications requiring low-latency processing and real-time analytics.

In contrast, while Cloud SQL is a relational database service, it is not tailored for real-time event-driven processing. Similarly, Cloud Functions provides a serverless execution environment for event-driven apps but is generally used for smaller tasks or as microservices rather than handling large-scale event processing. Cloud Storage, although useful for data storage, does not support real-time event processing directly, as it is primarily designed for storing and retrieving files rather than streaming data in real time.

Thus, Dataflow stands out as the technology best suited for building real-time event-driven architectures in Google Cloud.