Software Alternatives, Accelerators & Startups

Porter VS Metaflow

Compare Porter VS Metaflow and see what are their differences

Porter logo Porter

Heroku that runs in your own cloud

Metaflow logo Metaflow

Framework for real-life data science; build, improve, and operate end-to-end workflows.
  • Porter Landing page
    Landing page //
    2022-12-26
  • Metaflow Landing page
    Landing page //
    2023-03-03

Porter videos

Porter Robinson - Nurture ALBUM REVIEW

More videos:

  • Review - Porter app information and review in Hindi. ( Live Late night booking in Hyderabad)
  • Review - Are these the BEST Blank T-Shirts? (Rue Porter Review)

Metaflow videos

useR! 2020: End-to-end machine learning with Metaflow (S. Goyal, B. Galvin, J. Ge), tutorial

More videos:

  • Review - Screencast: Metaflow Sandbox Example

Category Popularity

0-100% (relative to Porter and Metaflow)
Developer Tools
100 100%
0% 0
Workflow Automation
0 0%
100% 100
Cloud Computing
100 100%
0% 0
DevOps Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Porter and Metaflow

Porter Reviews

We have no reviews of Porter yet.
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Metaflow Reviews

Comparison of Python pipeline packages: Airflow, Luigi, Gokart, Metaflow, Kedro, PipelineX
Metaflow enables you to define your pipeline as a child class of FlowSpec that includes class methods with step decorators in Python code.
Source: medium.com

Social recommendations and mentions

Based on our record, Metaflow should be more popular than Porter. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Porter mentions (4)

Metaflow mentions (12)

  • What are some open-source ML pipeline managers that are easy to use?
    I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home. Source: about 1 year ago
  • Needs advice for choosing tools for my team. We use AWS.
    1) I've been looking into [Metaflow](https://metaflow.org/), which connects nicely to AWS, does a lot of heavy lifting for you, including scheduling. Source: about 1 year ago
  • Selfhosted chatGPT with local contente
    Even for people who don't have an ML background there's now a lot of very fully-featured model deployment environments that allow self-hosting (kubeflow has a good self-hosting option, as do mlflow and metaflow), handle most of the complicated stuff involved in just deploying an individual model, and work pretty well off the shelf. Source: about 1 year ago
  • [OC] Gender diversity in Tech companies
    They had to figure out video compression that worked at the volume that they wanted to deliver. They had to build and maintain their own CDN to be able to have a always available and consistent viewing experience. Don’t even get me started on the resiliency tools like hystrix that they were kind enough to open source. I mean, they have their own fucking data science framework and they’re looking into using neural... Source: over 1 year ago
  • Going to Production with Github Actions, Metaflow and AWS SageMaker
    Github Actions, Metaflow and AWS SageMaker are awesome technologies by themselves however they are seldom used together in the same sentence, even less so in the same Machine Learning project. - Source: dev.to / almost 2 years ago
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What are some alternatives?

When comparing Porter and Metaflow, you can also consider the following products

Heroku - Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Render UIKit - React-inspired Swift library for writing UIKit UIs

Luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs.

DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.

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 ver...