Luigi VS Kazuhm
Compare Luigi VS Kazuhm and see what are their differences
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Luigi
Apache Airflow
Metaflow
Azkaban
Activeeon
Jenkins
Helios
StackStorm
Kazuhm
Activeeon
Mesosphere DCOS
Metaflow
DepHell
Rancher
Shipper.software
Amazon AWS
Kazuhm SaaS platform unifies the compute resources of an organization from desktops, to servers, to cloud, to edge, creating a private grid to place and process containerized workloads, optimize IT costs, security, and performance.
Through an easy user interface, customers leverage Kazuhm today to simplify Kubernetes and the deployment of popular data science applications, build their own private distributed compute networks, run workloads on-premises enabling the lowest possible latency, and easily manage multi-cloud and hybrid cloud environments.
Kubernetes-Made-Easy -- Set up and cluster deployment is super quick with container placement and host monitoring intuitively simple.
Multi-Cloud, Hybrid-Cloud Management -- Escape from vendor lock-in and centrally manage all your Public Cloud Hosts for FREE.
Data Science On Demand -- Simplify deployment of Spark and Jupyter and process workloads both on-premise and in the cloud.
Offset Cloud Costs -- Get “Cloud Smart”. Process containerized workloads on your Linux and Windows desktops and servers to offset cloud costs.
Low-Latency Workload Processing -- Reduce latency and improve performance by processing your data on-premise or at the edge – when milliseconds count.
Distributed Computing Anywhere -- Connect your desktops, both Windows and Linux, and servers or even your edge devices to create a powerful compute fabric.
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Based on our record, Luigi seems to be more popular. 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.
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 / 7 months ago
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
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 / almost 2 years ago
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
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: about 2 years ago
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
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.
Metaflow - Framework for real-life data science; build, improve, and operate end-to-end workflows.
Mesosphere DCOS - Mesosphere DCOS organizes your entire infrastructure as if it was a single computer.
Azkaban - Azkaban is a batch workflow job scheduler created at LinkedIn to run Hadoop jobs.
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...