metaflow VS wave

Compare metaflow vs wave and see what are their differences.

Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
metaflow wave
24 21
7,559 3,852
2.1% 1.0%
9.2 9.2
1 day ago 6 days ago
Python Python
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.

wave

Posts with mentions or reviews of wave. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-01.

What are some alternatives?

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

flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.

streamlit - Streamlit — A faster way to build and share data apps.

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

reactpy - It's React, but in Python

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]

gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

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

nicegui - Create web-based user interfaces with Python. The nice way.

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

dephell - :package: :fire: Python project management. Manage packages: convert between formats, lock, install, resolve, isolate, test, build graph, show outdated, audit. Manage venvs, build package, bump version.

dvc - 🦉 ML Experiments and Data Management with Git

pglet - Pglet - build internal web apps quickly in the language you already know!