Looking for something like Feathr? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 21 are open source.
Feathr provides enterprises with a platform for data engineering and AI workflows.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Kedro | — | Not stated | — |
| 2 | Deepchecks | — | Not stated | — |
| 3 | Kubeflow Pipelines | — | Yes | — |
| 4 | Primehub | — | Yes | — |
| 5 | CML | — | Yes | — |
| 6 | Aeromancy | — | Yes | — |
| 7 | Evidently | — | Yes | — |
| 8 | Featureform | — | Yes | — |
| 9 | DVC | — | Not stated | Web |
| 10 | PyTorch Lightning | — | Yes | — |
Kedro helps create reproducible, maintainable, and modular data science and data engineering pipelines.
Deepchecks tests and validates machine learning models and data, covering workflows from research through production.
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
PrimeHub offers an open-source platform for managing machine learning operations and workflows.
CML provides continuous machine learning and CI/CD workflows for machine learning projects.
Use Aeromancy to build reproducible machine learning workflows and projects.
Evidently evaluates, tests, and monitors machine learning systems and data pipelines.
Featureform turns existing data infrastructure into a virtual feature store.
Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.
PyTorch Lightning supports pretraining and fine tuning AI models across GPU setups.
Polyaxon describes its repository as infrastructure for AI orchestration and control.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
The ChefBoost Python framework supports decision trees such as ID3, C4.5, CART, CHAID, regression trees, and ensemble methods.
Ray provides an AI compute engine with a distributed runtime and libraries for machine learning workloads.
The Datumbox framework is written in Java for developing machine learning and statistical applications.
PyToune provides a simplified framework and utilities for working with PyTorch.
MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.
FLAML provides a fast Python library for automated machine learning and tuning.
The Feast repository describes an open source feature store for AI and machine learning projects.
FlexML offers an easy to use and flexible automated machine learning library for Python.
Ludwig provides a low code framework for building custom LLMs, neural networks, and other AI models.
ZenML provides a platform for machine learning pipelines and AI agents.
The goro project provides a high level machine learning library written for Go.
This Docker-based starter kit provides a runtime for machine learning work in Jupyter notebooks.
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
