datastrømbehandling
Datastrømbehandling, also known as stream processing, refers to the practice of processing data in motion. Unlike traditional batch processing where data is collected and processed in chunks at scheduled intervals, datastrømbehandling analyzes data as it is generated and arrives, often in real-time or near real-time. This approach is crucial for applications that require immediate insights and responses to rapidly changing data.
The core idea behind datastrømbehandling is to handle continuous, unbounded data sequences. This data can originate
Key characteristics of datastrømbehandling include low latency, high throughput, and fault tolerance. Systems designed for stream
Applications of datastrømbehandling are diverse and span numerous industries. Examples include real-time fraud detection in banking,