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Metaflow is an open-source Python and R framework that helps data scientists and engineers build, version, and run multi-step machine learning pipelines from a laptop to the cloud.

Mage provides a unified platform to build, schedule, monitor, and deliver data workflows that connect sources, transform data, and trigger actions across applications, APIs, and AI agents.

Luigi is a Python library that helps engineers build and manage complex batch job pipelines by automatically resolving task dependencies and handling failures.

Kestra is an open-source platform that orchestrates data, AI, infrastructure, and business workflows using a declarative, plugin-based control plane.

Open-source Kubernetes-native tools for application delivery, workflow orchestration, progressive deployment, and event-driven automation.

Flyte is an open-source platform for orchestrating machine learning and data processing workflows at scale, with native Kubernetes integration and a focus on reproducibility.

Apache DolphinScheduler is a distributed workflow scheduler that lets data engineers define, schedule, and monitor complex data pipelines across multiple processing engines.