What type of data is best suited for use in an IoT application?

In an IoT (Internet of Things) application, streaming data is particularly well-suited because it involves the continuous flow of information generated by connected devices and sensors in real time. IoT devices often produce large volumes of data quickly, and the ability to capture and process this data as it is generated is vital for timely insights and actions. Streaming data allows organizations to monitor conditions, make instant decisions, and respond promptly to changes, which is essential in various applications such as smart homes, industrial automation, and smart cities.

The dynamic nature of IoT environments means that immediate analysis and real-time response capabilities are necessary. Streaming data frameworks can handle this high-velocity data flow and facilitate real-time analytics and processing, which are critical for the effectiveness of IoT applications.

In contrast, batch data involves processing and analyzing data collected over a period of time, which is less suited for real-time needs. Relational data typically refers to structured data stored in tables with defined relationships, which might not capture the responsiveness required for IoT scenarios. Cognitive data pertains to data that is derived from machine learning and AI processes, focusing on understanding and interpreting data rather than real-time processing of generated information.