mlrun VS fds

Compare mlrun vs fds and see what are their differences.

fds

Fast Data Science, AKA fds, is a CLI for Data Scientists to version control data and code at once, by conveniently wrapping git and dvc (by DagsHub)
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mlrun fds
3 3
1,240 383
4.8% 0.8%
9.9 3.7
1 day ago 3 months ago
Python Python
Apache License 2.0 MIT License
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.

mlrun

Posts with mentions or reviews of mlrun. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-28.

fds

Posts with mentions or reviews of fds. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-28.
  • I reviewed 50+ open-source MLOps tools. Here’s the result
    3 projects | /r/mlops | 28 May 2022
    Also fds, it's an open source command line wrapper around Git and DVC.
  • Data Science Workflows — Notebook to Production
    7 projects | dev.to | 8 Feb 2022
    At DagsHub, we’re integrated with DVC, which I love using. First and foremost, it’s open-source. It provides pipeline capabilities and supports many cloud providers for remote storage. Also, DVC acts as an extension to Git, which allows you to keep using the standard Git flow in your work. If you don’t want to use both tools, I recommend using FDS, an open-source tool that makes version control for machine learning fast & easy. It combines Git and DVC under one roof and takes care of code, data, and model versioning. (Bias alert: DagsHub developed FDS)

What are some alternatives?

When comparing mlrun and fds you can also consider the following projects:

feast - Feature Store for Machine Learning

PyDrive2 - Google Drive API Python wrapper library. Maintained fork of PyDrive.

dagster-example-pipeline - Template Dagster repo using poetry and a single Docker container; works well with CICD

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

SmartSim - SmartSim Infrastructure Library.

phidata - Build AI Assistants with function calling and connect LLMs to external tools.

mosec - A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine

ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

Prefect - The easiest way to build, run, and monitor data pipelines at scale.

dvc - 🦉 ML Experiments and Data Management with Git

Keras - Deep Learning for humans

Media-Recommendation-Engine - A Recommendation Engine API that can be used to recommend movies, music, games, manga, anime, comics, tv shows and books. Deployed using an AWS EC2 instance.