Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
The Best MLRun Alternatives in 2026
Looking for something like MLRun? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 21 are open source.
MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.
Top picks at a glance
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Kubeflow Pipelines | — | Yes | — |
| 2 | Primehub | — | Yes | — |
| 3 | Tpot | — | Yes | — |
| 4 | ZenML | — | Yes | — |
| 5 | Datumbox | — | Yes | — |
| 6 | FLAML | — | Yes | — |
| 7 | Feast | — | Yes | — |
| 8 | FlexML | — | Yes | — |
| 9 | goro | — | Yes | — |
| 10 | Notebooks | — | Yes | — |
All MLRun alternatives
PrimeHub offers an open-source platform for managing machine learning operations and workflows.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
ZenML provides a platform for machine learning pipelines and AI agents.
The Datumbox framework is written in Java for developing machine learning and statistical applications.
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.
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.
Use Aeromancy to build reproducible machine learning workflows and projects.
The Feast project provides an open source feature store for AI and machine learning.
Evidently evaluates, tests, and monitors machine learning systems and data pipelines.
The ChefBoost Python framework supports decision trees such as ID3, C4.5, CART, CHAID, regression trees, and ensemble methods.
PyToune provides a simplified framework and utilities for working with PyTorch.
Featureform turns existing data infrastructure into a virtual feature store.
Deploy a ML inference service on a budget in less than 10 lines of code.
Ray provides an AI compute engine with a distributed runtime and libraries for machine learning workloads.
Deepchecks tests and validates machine learning models and data, covering workflows from research through production.
CML provides continuous machine learning and CI/CD workflows for machine learning projects.
Kedro
github.com/quantumblacklabs/kedroKedro helps create reproducible, maintainable, and modular data science and data engineering pipelines.
DVC
dvc.orgOpen-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.
Maze
github.com/enlite-ai/mazeMaze provides an applied reinforcement learning framework for developing projects in Python.
ClearML manages AI experiments, data, pipelines, orchestration, scheduling, and model serving in one MLOps platform.
Alternatives to similar tools
What is the best alternative to MLRun?
Are there open-source alternatives to MLRun?
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
























