Software Alternatives, Accelerators & Startups

Azure Data Factory VS Luigi

Compare Azure Data Factory VS Luigi and see what are their differences

Azure Data Factory logo Azure Data Factory

Learn more about Azure Data Factory, the easiest cloud-based hybrid data integration solution at an enterprise scale. Build data factories without the need to code.

Luigi logo Luigi

Luigi is a Python module that helps you build complex pipelines of batch jobs.
  • Azure Data Factory Landing page
    Landing page //
    2023-01-12
  • Luigi Landing page
    Landing page //
    2023-10-08

Azure Data Factory videos

Azure Data Factory Tutorial | Introduction to ETL in Azure

More videos:

  • Review - Use Azure Data Factory to copy and transform data
  • Review - Pass summit 2019: Head to Head, SSIS Versus Azure Data Factory

Luigi videos

Luigi's Mansion 3 Review

More videos:

  • Review - Luigi's Mansion 3 Review
  • Review - Luigi's Mansion 3 - REVIEW (Nintendo Switch)

Category Popularity

0-100% (relative to Azure Data Factory and Luigi)
ETL
100 100%
0% 0
Workflow Automation
39 39%
61% 61
Data Integration
100 100%
0% 0
Workflows
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 Azure Data Factory and Luigi

Azure Data Factory Reviews

15+ Best Cloud ETL Tools
Azure Data Factory is a fully managed, serverless data integration service by Azure Cloud. You can easily connect to more than 90 built-in data sources without any added cost, allowing for efficient data integration at an enterprise level. Azure's visual platform lets you create ETL and ELT processes without having to write any code.
Source: estuary.dev
Top 8 Apache Airflow Alternatives in 2024
While Apache Airflow focuses on creating tasks and building dependencies between them for workflow automation, Azure Data Factory is suitable for integration tasks. It would be a perfect fit for the construction of the ETL and ELT pipelines for data migration and integration across platforms.
Source: blog.skyvia.com
A List of The 16 Best ETL Tools And Why To Choose Them
Azure Data Factory is a cloud-based ETL service offered by Microsoft used to create workflows that move and transform data at scale.
Top Big Data Tools For 2021
Azure Data Factory is a cloud solution that enables you to integrate data between multiple relational and non-relational sources, transforming it according to your objectives and requirements.

Luigi Reviews

5 Airflow Alternatives for Data Orchestration
In this blog post, we will discuss five alternatives to manage workflows: Prefect, Dagster, Luigi, Mage AI, and Kedro. These tools can be used for any field, not just limited to data engineering. By understanding these tools, you'll be able to choose the one that best suits your data and machine learning workflow needs.
Top 8 Apache Airflow Alternatives in 2024
Even though Airflow and Luigi have much in common (open-source projects, Python used, Apache license), they have slightly different approaches to data workflow management. The first thing is that Luigi prevents tasks from running individually, which limits scalability. Moreover, Luigi’s API implements fewer features than that of Airflow, which might be especially difficult...
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
Among a popular choice for an Apache Airflow alternative is Luigi. It is a Python package that handles long-running batch processing. This means that it manages the automatic execution of data processing processes on several objects in a batch. A data processing job may be defined as a series of dependent tasks in Luigi.
Source: hevodata.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When does Luigi make sense? If you need to automate simple ETL processes (like logs) Luigi can handle them rapidly and without much setup. When it comes to complex tasks, Luigi is limited by its strict pipeline-like structure.
Source: www.xplenty.com
Comparison of Python pipeline packages: Airflow, Luigi, Gokart, Metaflow, Kedro, PipelineX
Luigi enables you to define your pipeline by child classes of Task with 3 class methods (requires, output, run) in Python code.
Source: medium.com

Social recommendations and mentions

Based on our record, Luigi should be more popular than Azure Data Factory. It has been mentiond 9 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.

Azure Data Factory mentions (3)

  • (Recommend) Fun Open Source Tool for Pushing Data Around
    You might want to look at Azure Data Factory https://azure.microsoft.com/en-us/services/data-factory/ to extend SSIS EDIT: Yes, I missed the "open source" part :). Source: about 2 years ago
  • Deploying Azure Data Factory using Bicep
    I'm also planning to do more content with Azure Data Factory, so I'd thought it be good to make a video combining the two. - Source: dev.to / almost 3 years ago
  • Class construction help
    Or, if oyu are using azure then azure data factory https://azure.microsoft.com/en-us/services/data-factory/. Source: almost 3 years ago

Luigi mentions (9)

  • Ask HN: What is the correct way to deal with pipelines?
    I agree there are many options in this space. Two others to consider: - https://airflow.apache.org/ - https://github.com/spotify/luigi There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file... - Source: Hacker News / 8 months ago
  • In the context of Python what is a Bob Job?
    Maybe if your use case is “smallish” and doesn’t require the whole studio suite you could check out apscheduler for doing python “tasks” on a schedule and luigi to build pipelines. Source: almost 2 years ago
  • Lessons Learned from Running Apache Airflow at Scale
    What are you trying to do? Distributed scheduler with a single instance? No database? Are you sure you don't just mean "a scheduler" ala Luigi? https://github.com/spotify/luigi. - Source: Hacker News / about 2 years ago
  • Apache Airflow. How to make the complex workflow as an easy job
    It's good to know what Airflow is not the only one on the market. There are Dagster and Spotify Luigi and others. But they have different pros and cons, be sure that you did a good investigation on the market to choose the best suitable tool for your tasks. - Source: dev.to / over 2 years ago
  • DevOps Fundamentals for Deep Learning Engineers
    MLOps is a HUGE area to explore, and not surprisingly, there are many startups showing up in this space. If you want to get it on the latest trends, then I would look at workflow orchestration frameworks such as Metaflow (started off at Netflix, is now spinning off into its own enterprise business, https://metaflow.org/), Kubeflow (used at Google, https://www.kubeflow.org/), Airflow (used at Airbnb,... Source: over 2 years ago
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What are some alternatives?

When comparing Azure Data Factory and Luigi, you can also consider the following products

Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data.

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

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”.

Kestra.io - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.

DataTap - Adverity is the best data intelligence software for data-driven decision making. Connect to all your sources and harmonize the data across all channels.

Dagster - The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.