What is Stream Processing?

Stream processing is the continuous ingestion and analysis of data as it’s generated, enabling applications to act on real-time information instead of waiting for batch jobs to finish.

Unlike batch processing, which handles static data in scheduled chunks, stream processing operates on continuous data flows to deliver low-latency insights.

Typical applications include fraud detection, IoT monitoring, real-time analytics, and personalized recommendations driven by live user interactions.

It eliminates latency between data generation and action, ensuring immediate responses, consistent insights, and improved decision-making.

Atlas Stream Processing unifies real-time and historical data in one platform, letting developers use the same MongoDB Query API for streaming and stored data.