Real-time Data Streams
Real-time data streams refer to continuous flows of data that are generated, processed, and delivered with minimal latency, typically in milliseconds or seconds. This concept involves technologies and architectures that handle data as it is produced, enabling immediate analysis, monitoring, and action. It is fundamental in applications requiring up-to-the-second insights, such as financial trading, IoT sensor monitoring, and live user interactions.
Developers should learn about real-time data streams when building systems that require instant data processing, such as fraud detection, real-time analytics, or live dashboards. It is essential for use cases like streaming video, social media feeds, and operational monitoring where delays can impact user experience or decision-making. Mastering this concept helps in designing scalable, low-latency architectures using tools like Apache Kafka or Apache Flink.