Adatfolyamfeldolgozó

Adatfolyamfeldolgozó is a Hungarian term that translates to "data stream processor" in English. It refers to a system or software designed to process data in real-time as it is generated and arrives in a continuous flow. Unlike traditional batch processing, which analyzes data in discrete chunks after it has been collected, data stream processing handles data continuously, allowing for immediate analysis and reaction.

These systems are crucial for applications that require low latency and up-to-the-minute insights. Examples include financial trading platforms monitoring stock prices, fraud detection systems analyzing credit card transactions as they occur, or IoT devices collecting sensor data from machinery and reacting to anomalies instantly.

Key characteristics of adatfolyamfeldolgozó include its ability to handle high volumes of data, its fault tolerance to ensure continuous operation, and its capacity for complex event processing, which involves identifying patterns and relationships within the data streams. Technologies like Apache Kafka, Apache Flink, and Apache Spark Streaming are commonly used to implement data stream processing solutions. The goal is to extract value and make decisions from data without delay, enabling more dynamic and responsive applications.