concept

Data Streams

Data streams refer to continuous, real-time sequences of data records that are generated and processed incrementally, often from sources like sensors, logs, or user interactions. This concept is central to stream processing, where data is analyzed on-the-fly as it arrives, enabling immediate insights and actions. It contrasts with batch processing, which handles data in large, static chunks.

Also known as: Streaming Data, Real-time Data, Event Streams, Data Pipelines, Continuous Data
🧊Why learn Data Streams?

Developers should learn about data streams when building applications that require real-time analytics, monitoring, or event-driven architectures, such as fraud detection, IoT systems, or live dashboards. It's essential for handling high-velocity data where low latency is critical, allowing systems to react instantly to new information without waiting for batch updates.

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