Software Alternatives & Reviews

CloudReactor VS Metaflow

Compare CloudReactor VS Metaflow and see what are their differences

CloudReactor logo CloudReactor

Easily deploy, schedule, manage and monitor tasks and workflows. Create complex workflows in seconds. Deploy tasks to AWS.

Metaflow logo Metaflow

Framework for real-life data science; build, improve, and operate end-to-end workflows.
  • CloudReactor Landing page
    Landing page //
    2021-11-19
  • Metaflow Landing page
    Landing page //
    2023-03-03

CloudReactor 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 CloudReactor and Metaflow)
Automation
100 100%
0% 0
Workflow Automation
24 24%
76% 76
DevOps Tools
0 0%
100% 100
Workflows
27 27%
73% 73

User comments

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Reviews

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

CloudReactor Reviews

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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 seems to be a lot more popular than CloudReactor. While we know about 12 links to Metaflow, we've tracked only 1 mention of CloudReactor. 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.

CloudReactor mentions (1)

  • Now a good time to move away from Elastic Beanstalk in production. Looking at moving to EKS or ECS
    I am also a fan of ECS because of its simplicity and integration with AWS security groups, roles, and VPC. That is why I made it the primary execution method of a monitoring and management tool I created: CloudReactor (https://cloudreactor.io). Source: about 3 years 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: 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 / over 1 year ago
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What are some alternatives?

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

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

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

Workato - Experts agree - we're the leader. Forrester Research names Workato a Leader in iPaaS for Dynamic Integration. Get the report. Gartner recognizes Workato as a “Cool Vendor in Social Software and Collaboration”.

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...

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

Activeeon - ProActive Workflows & Scheduling is a java-based cross-platform workflow scheduler and resource manager that is able to run workflow tasks in multiple languages and multiple environments: Windows, Linux, Mac, Unix, etc.