Software Alternatives, Accelerators & Startups

Hamilton VS Metaflow

Compare Hamilton VS Metaflow and see what are their differences

Hamilton logo Hamilton

A scalable general purpose micro-framework for defining dataflows. You can use it to build dataframes, numpy matrices, python objects, ML models, etc. Embed Hamilton anywhere python runs, e.g. spar...

Metaflow logo Metaflow

Framework for real-life data science; build, improve, and operate end-to-end workflows.
  • Hamilton Landing page
    Landing page //
    2023-09-21
  • Metaflow Landing page
    Landing page //
    2023-03-03

Hamilton videos

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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 Hamilton and Metaflow)
Application And Data
100 100%
0% 0
DevOps Tools
0 0%
100% 100
Languages & Frameworks
100 100%
0% 0
Workflow Automation
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 Hamilton and Metaflow

Hamilton Reviews

We have no reviews of Hamilton 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 Hamilton. 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.

Hamilton mentions (5)

  • Show HN: Hamilton's UI – observability, lineage, and catalog for data pipelines
    Hey HN – Stefan and Elijah here from DAGWorks (http://dagworks.io/), we’re the authors of Hamilton (https://github.com/dagworks-inc/hamilton), an open-source library for building self-documenting, modular dataflows in python that works for data, ML, LLM pipelines, & even web-workflows. We’ve been developing this UI for a while and we’re excited to say we... - Source: Hacker News / about 1 month ago
  • Using IPython Jupyter Magic commands to improve the notebook experience
    In this post, we’ll show how your team can turn any utility function(s) into reusable IPython Jupyter magics for a better notebook experience. As an example, we’ll use Hamilton, my open source library, to motivate the creation of a magic that facilitates better development ergonomics for using it. You needn’t know what Hamilton is to understand this post. - Source: dev.to / 3 months ago
  • Free access to beta product I'm building that I'd love feedback on
    This is me. I drive an open source library Hamilton that people doing time-series/ML work love to use. I'm building a paid product around it at DAGWorks, and I'm after feedback on our current version. Can I entice anyone to:. Source: about 1 year ago
  • IPyflow: Reactive Python Notebooks in Jupyter(Lab)
    From a nuts and bolts perspective, I've been thinking of building some reactivity on top of https://github.com/dagworks-inc/hamilton (author here) that could get at this. (If you have a use case that could be documented, I'd appreciate it.). - Source: Hacker News / about 1 year ago
  • Needs advice for choosing tools for my team. We use AWS.
    Otherwise, I'm biased here, but check out https://github.com/dagworks-inc/hamilton - it could be your universal layer that expresses how things should flow, that is orchestration system agnostic, which would make it easy to migrate between systems easily. Source: about 1 year ago

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: over 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 Hamilton and Metaflow, you can also consider the following products

Observable - Interactive code examples/posts

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

Django REST framework - Django REST framework is a toolkit for building web APIs.

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

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Azkaban - Azkaban is a batch workflow job scheduler created at LinkedIn to run Hadoop jobs.