concept

Stream Processing

Stream processing is a computing paradigm that involves continuously processing data in real-time as it is generated or received, rather than in batches. It enables applications to handle high-velocity data streams, such as from sensors, logs, or financial transactions, with low latency. This approach is essential for scenarios requiring immediate insights, alerts, or actions based on live data.

Also known as: Real-time processing, Event stream processing, Data streaming, Continuous processing, ESP
🧊Why learn Stream Processing?

Developers should learn stream processing for building real-time analytics, monitoring systems, fraud detection, and IoT applications where data arrives continuously and needs immediate processing. It is crucial in industries like finance for stock trading, e-commerce for personalized recommendations, and telecommunications for network monitoring, as it allows for timely decision-making and reduces storage costs by processing data on-the-fly.

Compare Stream Processing

Learning Resources

Related Tools

Alternatives to Stream Processing