Description: The streaming model in data processing refers to a design pattern that allows building applications that process data streams in real-time. Unlike batch processing, where data is collected and processed in intervals, streaming enables continuous analysis of data as it arrives. This is especially relevant in a world where speed and immediacy are crucial. Streaming frameworks stand out for their ability to handle large volumes of data in real-time, offering features such as fault tolerance, event-time processing, and the ability to perform complex operations on data streams. Their architecture allows applications to run in both cloud and on-premises environments, facilitating integration with other tools and systems. Additionally, these frameworks provide an intuitive programming model that enables developers to create streaming applications efficiently, using high-level APIs that simplify real-time data handling. In summary, the streaming model is fundamental for developing modern applications that require instant data processing and continuous analysis, making it an essential tool in the realm of big data and advanced analytics.
