streamingpipeline
A streaming pipeline is a data processing architecture designed to continuously ingest, process, and deliver data as it arrives, typically with low latency. It handles data in motion rather than in discrete batches, enabling real-time or near-real-time insights and actions.
Core components include data sources or producers that generate events, a transport layer such as a message
Processing semantics in streaming pipelines often involve event-time processing with watermarks to handle out-of-order events, windowing
Design considerations include handling schema evolution, ensuring idempotent sinks, managing backpressure, and scaling through parallelism. Pipelines
Common use cases encompass real-time analytics, monitoring and alerting, fraud detection, and streaming ETL for data