Here’s the difference between Airflow and Kubeflow. The comparison is based on pricing, deployment, business model, and other important factors.
Apache Airflow is a workflow automation and scheduling system that can be used to author and manage data pipelines. Airflow uses workflows made of directed acyclic graphs (DAGs) of tasks.
Kubeflow provides an open-source machine learning toolkit for Kubernetes. Enables users to train, deploy and manage a machine learning stack on Kubernetes. Is compatible with PyTorch, Apache MXNet, MPI, XGBoost, Chainer & more and can be integrated with Istio and Ambassador.