dumbo VS luigi

Compare dumbo vs luigi and see what are their differences.

dumbo

Python module that allows one to easily write and run Hadoop programs. (by klbostee)

luigi

Luigi 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. (by spotify)
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dumbo luigi
0 13
1,047 15,992
- 0.8%
0.0 7.4
over 4 years ago 6 days ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

dumbo

Posts with mentions or reviews of dumbo. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning dumbo yet.
Tracking mentions began in Dec 2020.

luigi

Posts with mentions or reviews of luigi. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-07-10.
  • In the context of Python what is a Bob Job?
    2 projects | reddit.com/r/learnpython | 10 Jul 2022
    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.
  • Lessons Learned from Running Apache Airflow at Scale
    12 projects | news.ycombinator.com | 23 May 2022
    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
  • DevOps Fundamentals for Deep Learning Engineers
    6 projects | reddit.com/r/deeplearning | 20 Feb 2022
    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, https://airflow.apache.org/), and Luigi (used at Spotify, https://github.com/spotify/luigi). Then you have the model serving itself, so there is Seldon (https://www.seldon.io/), Torchserve (https://pytorch.org/serve/), and TensorFlow Serving (https://www.tensorflow.org/tfx/guide/serving). You also have the actual export and transfer of DL models, and ONNX is the most popular here (https://onnx.ai/). Spark (https://spark.apache.org/) still holds up nicely after all these years, especially if you are doing batch predictions on massive amount of data. There is also the GitFlow way of doing things and Data Version Control (DVC, https://dvc.org/) is taken a pole position there.
  • Data pipelines with Luigi
    4 projects | dev.to | 22 Dec 2021
    At Wonderflow we're doing a lot of ML / NLP using Python and recently we are enjoying writing data pipelines using Spotify's Luigi.
  • Noobie who is trying to use K8s needs confirmation to know if this is the way or he is overestimating Kubernetes.
    3 projects | reddit.com/r/kubernetes | 20 Oct 2021
  • Open Source ETL Project For Startups
    3 projects | dev.to | 22 Sep 2021
    💡【About Luigi】 https://github.com/spotify/luigi Luigi was built at Spotify since 2012, it's open source and mainly used for getting data insights by showing recommendations, toplists, A/B test analysis, external reports, internal dashboards, etc.
  • Using Terraform to make my many side-projects 'pick up and play'
    3 projects | dev.to | 14 Jun 2021
    So to sum that up, I went from having nothing for my side-project set up in AWS to having a Kubernetes cluster with the basic metrics and dashboard, a proper IAM-linked ServiceAccount support for a smooth IAM experience in K8s, and Luigi deployed so that I could then run a Luigi workflow using an ad-hoc run of a CronJob. That's quite remarkable to me. All that took hours to figure out and define when I first did it, over six months ago.
  • PyPy Project looking for sponsorship to add support for Apple Silicon
    5 projects | news.ycombinator.com | 31 Dec 2020
    I used Luigi [1] to automate data processing at a previous job. It's a simple job queue with a UI. You request jobs from it, and then run them for minutes or hours, so it shouldn't normally be a bottleneck and it makes sense to use a language that's quick and easy to write.

    It's written in Python and works fine to process thousands of jobs per day. Once you start having tens of thousands of jobs in the queue, it gets slow enough that it can back things up. This compounds the problem, eventually resulting in the whole thing crashing.

    By switching the interpreter to PyPy, I was able to keep the data pipeline running at that scale without having to rewrite anything.

    [1] https://github.com/spotify/luigi

What are some alternatives?

When comparing dumbo and luigi you can also consider the following projects:

Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Kedro - A Python framework for creating reproducible, maintainable and modular data science code.

Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing

mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services

Pinball

streamparse - Run Python in Apache Storm topologies. Pythonic API, CLI tooling, and a topology DSL.

Dask - Parallel computing with task scheduling

BPMN_RPA - Robotic Process Automation in Windows and Linux by using Diagrams.net BPMN diagrams.

dpark - Python clone of Spark, a MapReduce alike framework in Python