Andmevoogude

Andmevoogude, often translated as data streams, refers to a continuous sequence of data that is generated and processed over time. Unlike traditional batch processing where data is collected and processed in discrete chunks, data streams are handled in real-time or near real-time as they arrive. This paradigm is crucial for applications requiring immediate insights and responses to rapidly changing information.

The concept of data streams is fundamental to many modern technologies. Examples include sensor data from IoT devices, financial transaction logs, social media feeds, website clickstreams, and network traffic monitoring. The inherent characteristic of data streams is their unbounded nature; they are potentially infinite and constantly evolving.

Processing data streams involves specialized techniques and architectures designed for high throughput and low latency. This can include technologies like Apache Kafka, Apache Flink, and Apache Spark Streaming. These systems allow for the ingestion, transformation, analysis, and storage of data as it flows, enabling functionalities such as real-time anomaly detection, predictive analytics, and dynamic dashboard updates. The ability to react to events as they happen is a key differentiator of data stream processing.