Overview

Red Hat OpenShift

Stacks1.5K

Followers1.4K

Votes517

GitHub Stars885

Forks510

Domino

Stacks24

Followers29

Votes0

Domino vs OpenShift: What are the differences?

Deployment Model: One key difference between Domino and OpenShift is the deployment model they follow. Domino offers a more managed and controlled environment for deploying data science models and workflows, focusing on reproducibility and collaboration. On the other hand, OpenShift is more versatile and allows for deploying a wide range of applications in various environments, offering greater flexibility in deployment options.
Focus: Another significant difference between Domino and OpenShift is their primary focus. Domino is specifically designed for data science teams and focuses on providing tools and features tailored to the needs of data scientists, such as version control, reproducibility, and collaboration. OpenShift, on the other hand, is more general-purpose and caters to a broader range of applications beyond data science, offering features for DevOps, microservices, and container orchestrations.
Scalability: When it comes to scalability, Domino and OpenShift differ in their approach. Domino is optimized for scaling data science workloads efficiently, allowing users to run complex computations on large datasets with ease. OpenShift, on the other hand, is built for scaling applications across clusters of containers, providing more robust scalability options for enterprise-level deployments.
Community Support: The level of community support for Domino and OpenShift also sets them apart. Domino has a smaller but dedicated community of data scientists and researchers who contribute resources and best practices specific to data science workflows. OpenShift, being an open-source platform, benefits from a larger community of developers and contributors, offering a broader range of plugins, extensions, and integrations.
Workflow Automation: Domino and OpenShift differ in their approach to workflow automation. Domino emphasizes automation and reproducibility in data science workflows, providing tools for automated versioning, experimentation tracking, and model deployment. OpenShift focuses more on automating the deployment, scaling, and management of applications across containerized environments, with features like auto-scaling, self-healing, and continuous integration/continuous deployment (CI/CD) pipelines.
Cost Structure: Lastly, the cost structure of Domino and OpenShift varies significantly. Domino typically follows a subscription-based pricing model with tiered pricing plans based on the number of users and computational resources required. OpenShift offers a flexible pricing model based on resource usage, with options for self-managed and managed services, allowing users to pay only for the resources they consume.

In Summary, Domino and OpenShift differ in their deployment models, focus, scalability, community support, workflow automation, and cost structure.

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Detailed Comparison

Red Hat OpenShift	Domino
OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.	Use our cloud-hosted infrastructure to securely run your code on powerful hardware with a single command — without any changes to your code. If you have your own infrastructure, our Enterprise offering provides powerful, easy-to-use cluster management functionality behind your firewall.
Built-in support for Node.js, Ruby, Python, PHP, Perl, and Java (the standard in today's Enterprise);OpenShift is extensible with a customizable cartridge functionality that allows developers to add any other language they wish. We've seen everything from Clojure to Cobol running on OpenShift;OpenShift supports frameworks ranging from Spring, to Rails, to Play;Autoscaling- OpenShift can scale your application by adding additional instances of your application and enabling clustering. Alternatively, you can manually scale the amount of resources with which your application is deployed when needed;OpenShift by Red Hat is built on open-source technologies (Red Hat Enterprise Linux- RHEL);One Click Deployment- Deploying to the OpenShift platform is as easy a clicking a button or entering a "Git push" command	Domino Cloud supports the most powerful data analysis languages — Python, R, MATLAB, and Julia;Modern and powerful cluster management;Use a single-core machine during development; then, with one click, scale up to a 32-core machine to crunch through that data quickly;Domino installs, maintains, and updates common platform dependencies so you never get stuck in “version hell” again;Domino automatically keeps a revisioned history of all three — code, data, and results — so you can always reproduce past work;Easy synchronization, Email notifications & reports, and Discusscussions
Statistics
GitHub Stars 885	GitHub Stars -
GitHub Forks 510	GitHub Forks -
Stacks 1.5K	Stacks 24
Followers 1.4K	Followers 29
Votes 517	Votes 0
Pros & Cons
Pros 99 Good free plan 63 Open Source 47 Easy setup 43 Nodejs support 42 Well documented Cons 2 Decisions are made for you, limiting your options 2 License cost 1 Behind, sometimes severely, the upstreams	No community feedback yet

What are some alternatives to Red Hat OpenShift, Domino?

Heroku

Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling.

Clever Cloud

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Google App Engine

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AWS Elastic Beanstalk

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Render

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Hasura

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Cloud 66

Cloud 66 gives you everything you need to build, deploy and maintain your applications on any cloud, without the headache of dealing with "server stuff". Frameworks: Ruby on Rails, Node.js, Jamstack, Laravel, GoLang, and more.

Jelastic

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Dokku

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PythonAnywhere

It's somewhat unique. A small PaaS that supports web apps (Python only) as well as scheduled jobs with shell access. It is an expensive way to tinker and run several small apps.