Dnew

Dnew is a fictional term used in this article to illustrate a data-processing framework. It is described as a declarative dataflow language and runtime for building streaming and batch pipelines.

Pipelines in Dnew are defined as graphs of operators with explicit sources, transforms, and sinks. The language emphasizes deterministic execution, backpressure, windowing, and event-time processing, while supporting structured records and basic scalar types.

Architecturally, Dnew comprises a declarative language, a compiler, and a portable runtime. The compiler translates programs into an intermediate representation that can be executed by backends ranging from in-memory engines to distributed clusters. It provides fault tolerance, state management, and checkpointing to enable reliable long-running jobs.

Dnew originated through a collaboration of researchers and practitioners and was released as an open-source project with a community-governed development model. The project adopts a permissive license and welcomes contributions, documentation improvements, and educational use.

In practice, Dnew has seen use in academic demonstrations and early industry pilots. Supporters highlight its readability and modularity, while critics point to a relatively small ecosystem of tooling and adapters and a learning curve compared with established data pipelines.

Related topics include dataflow languages, stream processing frameworks, and data engineering platforms.