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Apache Airflow is an open-source workflow management platform for data engineering pipelines. It started at Airbnb in October 2014 [2] as a solution to manage the company's increasingly complex workflows. Creating Airflow allowed Airbnb to programmatically author and schedule their workflows and monitor them via the built-in Airflow user interface.
Whenever a new workflow with all components is shared via GitHub, anyone can try it on a different machine, with different environment and using slightly different choices (compilers, libraries, data sets). Whenever an unexpected or wrong behavior is encountered, the community explains it, fixes components and shares them back as described in. [4]
VisTrails is a new system that provides provenance management support for exploratory computational tasks. It combines features of workflow and visualization systems. Similar to workflow systems, it allows the combination of loosely coupled resources, specialized libraries, and grid and Web services.
Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.
Celery is written in Python, but the protocol can be implemented in any language.It can also operate with other languages using webhooks. [4] There is also a Ruby-Client called RCelery, [5] a PHP client, [6] a Go client, [7] a Rust client, [8] and a Node.js client.
Workflows are computational analyses that specify all the steps (and parameters) in the analysis, but none of the data. Workflows are used to run the same analysis against multiple sets of input data. Galaxy is a scientific workflow system. These systems provide a means to build multi-step computational analyses akin to a recipe.
StackStorm (abbreviation: ST2) is an open source event-driven platform for runbook automation. It supports the Infrastructure as Code (IaC) approach to DevOps automation and has been compared with SaltStack and Ansible, [2] it primarily focuses on doing things or running workflows based on events.
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.