What is the primary characteristic of streaming data?

Streaming data is fundamentally characterized as being continuous with no defined start or stop. This type of data flows in real time, comprising an ongoing sequence of events or information that is transmitted as it is generated.

In various applications, such as social media feeds or sensor readings, streaming data can be consistently inputted into systems, making it crucial for scenarios where immediate insights and real-time analysis are necessary. For example, stock market data or live traffic updates are prime examples of streaming data as they provide a continuous flow of information, which can change at any moment.

This contrastingly highlights batch processing, where data is collected over a period and processed collectively, leading to distinct starting and ending points. This is not characteristic of streaming data. Additionally, while streaming data can originate from IoT devices, it is not exclusively generated by them; any source that produces data on a continuous basis, such as servers logging events, is also relevant. Thus, the defining trait of streaming data remains its continuous nature.