What ensures that stream processing handles data in real-time?

The choice indicating that data is processed continually as it arrives highlights a fundamental characteristic of stream processing. Stream processing is designed to handle data in a real-time manner, meaning that the system ingests, processes, and outputs data almost instantaneously as it flows through the system. This contrasts significantly with batch processing, where data is collected over a period and only processed after the collection is complete.

In stream processing, as new data enters the system, it is acted upon immediately. This capability allows for timely insights, enabling users and systems to react quickly to data as it becomes available. This characteristic is particularly important for applications that require immediate decision-making based on incoming data, such as fraud detection, real-time analytics, or live data monitoring.

While other options touch on aspects that might support performance or processing efficiency, they do not specifically capture the essence of what stream processing entails. Continuous availability of computing resources is vital but does not alone ensure real-time processing. Similarly, using stored procedures for data aggregation may be beneficial in certain contexts but does not inherently describe the real-time nature of stream processing nor its operational mechanism.