Data streaming is the continuous transmission of data in real-time or near-real-time from a source to a destination, allowing data to be processed or analyzed as it arrives.
Key Characteristics:
Real-time or near real-time: Unlike batch processing, which handles data in large chunks after collection, streaming deals with data immediately.
Continuous flow: Data flows endlessly from sources such as sensors, user activity, financial transactions, or server logs.
Low latency: It supports rapid insights, such as fraud detection or live analytics.
Common Use Cases:
Monitoring stock prices or weather data
Real-time fraud detection in banking
Streaming video/audio (e.g., Netflix, Spotify)
IoT sensor data processing
Web clickstream analysis
Technologies:
Apache Kafka, Apache Flink, Apache Spark Streaming, and Amazon Kinesis are popular tools for building data streaming applications.
