metaflow VS flyte

Compare metaflow vs flyte and see what are their differences.

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metaflow flyte
24 31
7,559 4,727
2.1% 3.0%
9.2 9.8
1 day ago about 12 hours ago
Python Go
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

metaflow

Posts with mentions or reviews of metaflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-05.

flyte

Posts with mentions or reviews of flyte. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-15.

What are some alternatives?

When comparing metaflow and flyte you can also consider the following projects:

zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

argo - Workflow Engine for Kubernetes

pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]

temporal - Temporal service

kedro-great - The easiest way to integrate Kedro and Great Expectations

kubeflow - Machine Learning Toolkit for Kubernetes

clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

Celery-Kubernetes-Operator - An operator to manage celery clusters on Kubernetes (Work in Progress)

dvc - 🦉 ML Experiments and Data Management with Git

Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

great_expectations - Always know what to expect from your data.

hera - Hera is an Argo Python SDK. Hera aims to make construction and submission of various Argo Project resources easy and accessible to everyone! Hera abstracts away low-level setup details while still maintaining a consistent vocabulary with Argo. ⭐️ Remember to star!