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  1. Stackups
  2. Utilities
  3. Task Scheduling
  4. Workflow Manager
  5. Luigi vs Metaflow

Luigi vs Metaflow

OverviewDecisionsComparisonAlternatives

Overview

Luigi
Luigi
Stacks78
Followers211
Votes9
GitHub Stars18.5K
Forks2.4K
Metaflow
Metaflow
Stacks16
Followers51
Votes0
GitHub Stars9.6K
Forks930

Luigi vs Metaflow: What are the differences?

Introduction

In this comparison, we will highlight the key differences between Luigi and Metaflow, two popular workflow management tools.

  1. Programming Paradigm: Luigi primarily relies on Python for defining workflows in a script-like manner, whereas Metaflow is designed around the concept of "flow" where a flow is a python class with methods that define various steps of the workflow.

  2. Ease of Use: Luigi provides a simple interface and is easy to set up for basic tasks, while Metaflow is more suitable for complex workflows due to its strong integration with AWS and support for data science needs.

  3. Scalability: Luigi is better suited for smaller workflows or projects with limited scalability requirements, while Metaflow is designed to handle large-scale workflows efficiently, making it ideal for enterprise-level projects.

  4. Monitoring and Visualization: Metaflow offers built-in tools for easy monitoring and visualization of workflow steps, metrics, and dependencies, providing a comprehensive view of the workflow's progress and performance compared to Luigi.

  5. Support for Data Science: Metaflow is specifically tailored for data science projects, with features like easy experiment tracking, versioning, and integration with popular data science libraries, making it the preferred choice for data-focused workflows over Luigi.

  6. Integration with Data Stores: Metaflow seamlessly integrates with popular data storage technologies like AWS S3, while Luigi provides flexibility to work with different storage systems but may require additional configuration and setup for seamless integration.

In Summary, Luigi and Metaflow offer distinct advantages in workflow management, with Luigi being more straightforward for simpler tasks and Metaflow excelling in scalability and support for data science projects.

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Advice on Luigi, Metaflow

Anonymous
Anonymous

Jan 19, 2020

Needs advice

I am so confused. I need a tool that will allow me to go to about 10 different URLs to get a list of objects. Those object lists will be hundreds or thousands in length. I then need to get detailed data lists about each object. Those detailed data lists can have hundreds of elements that could be map/reduced somehow. My batch process dies sometimes halfway through which means hours of processing gone, i.e. time wasted. I need something like a directed graph that will keep results of successful data collection and allow me either pragmatically or manually to retry the failed ones some way (0 - forever) times. I want it to then process all the ones that have succeeded or been effectively ignored and load the data store with the aggregation of some couple thousand data-points. I know hitting this many endpoints is not a good practice but I can't put collectors on all the endpoints or anything like that. It is pretty much the only way to get the data.

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Comments

Detailed Comparison

Luigi
Luigi
Metaflow
Metaflow

It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

It is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. It was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.

dependency resolution; workflow management; visualization
End-to-end ML Platform; Model with your favorite tools; Powered by the AWS cloud; Battle-hardened at Netflix
Statistics
GitHub Stars
18.5K
GitHub Stars
9.6K
GitHub Forks
2.4K
GitHub Forks
930
Stacks
78
Stacks
16
Followers
211
Followers
51
Votes
9
Votes
0
Pros & Cons
Pros
  • 5
    Hadoop Support
  • 3
    Python
  • 1
    Open soure
No community feedback yet
Integrations
Hadoop
Hadoop
Python
Python
No integrations available

What are some alternatives to Luigi, Metaflow?

Airflow

Airflow

Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.

GitHub Actions

GitHub Actions

It makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Make code reviews, branch management, and issue triaging work the way you want.

Pandas

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

NumPy

NumPy

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

Apache Beam

Apache Beam

It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.

Zenaton

Zenaton

Developer framework to orchestrate multiple services and APIs into your software application using logic triggered by events and time. Build ETL processes, A/B testing, real-time alerts and personalized user experiences with custom logic.

PyXLL

PyXLL

Integrate Python into Microsoft Excel. Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python. Works with all 3rd party and open source Python packages. No need to write any VBA!

Unito

Unito

Build and map powerful workflows across tools to save your team time. No coding required. Create rules to define what information flows between each of your tools, in minutes.

Shipyard

Shipyard

na

PromptX

PromptX

PromptX is an AI-powered enterprise knowledge and workflow platform that helps organizations search, discover and act on information with speed and accuracy. It unifies data from SharePoint, Google Drive, email, cloud systems and legacy databases into one secure Enterprise Knowledge System. Using generative and agentic AI, users can ask natural language questions and receive context-rich, verifiable answers in seconds. PromptX ingests and enriches content with semantic tagging, entity recognition and knowledge cards, turning unstructured data into actionable insights. With adaptive prompts, collaborative workspaces and AI-driven workflows, teams make faster, data-backed decisions. The platform includes RBAC, SSO, audit trails and compliance-ready AI governance, and integrates with any LLM or external search engine. It supports cloud, hybrid and on-premise deployments for healthcare, public sector, finance and enterprise service providers. PromptX converts disconnected data into trusted and actionable intelligence, bringing search, collaboration and automation into a single unified experience.

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