Real-Time Data Ingestion and Streaming Pipelines

The rise of streaming technologies has spurred the emergence of real-time data ingestion and streaming pipelines, which serve as the foundation for building streaming data platforms. Real-time data ingestion focuses on collecting, validating, and transforming data as it becomes available. A streaming pipeline consists of a series of data transformation steps applied to streams of data—effectively a set of streaming ETL processes. Both concepts are wide in scope and can be addressed along various dimensions, including protocol semantics and guarantees; data serialization formats; support for schema evolution and data quality; pipeline architectures; data transformation and enrichment such as windowing, aggregation, and complex event processing; durable storage; and consistent state management. Real-time data processing is acknowledged as a rapidly maturing field of research and engineering practice.