summingbird

Enables writing data processing logic once and running it on both batch (Scalding) and real-time (Storm) engines, as demonstrated in the word count example where the same code works for multiple modes.

Uses Scala/Java collection transformations like flatMap and sumByKey, making code intuitive for developers; the README shows how Summingbird code closely mirrors native Scala collections.

Supports hybrid execution that combines batch and real-time processing for robust data consistency, offering production-ready primitives to build fault-tolerant systems as highlighted in the features.

Abstracts underlying platforms such as Storm and Scalding, allowing business logic to remain decoupled from execution engines, which simplifies code reuse across different processing contexts.