Google App Engine vs OpenShift: What are the differences?
Developers describe Google App Engine as "Build web applications on the same scalable systems that power Google applications". Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow. On the other hand, OpenShift is detailed as "Red Hat's free Platform as a Service (PaaS) for hosting Java, PHP, Ruby, Python, Node.js, and Perl apps". 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.
Google App Engine and OpenShift belong to "Platform as a Service" category of the tech stack.
Some of the features offered by Google App Engine are:
- Zero to sixty: Scale your app automatically without worrying about managing machines.
- Supercharged APIs: Supercharge your app with services such as Task Queue, XMPP, and Cloud SQL, all powered by the same infrastructure that powers the Google services you use every day.
- You're in control: Manage your application with a simple, web-based dashboard allowing you to customize your app's performance.
On the other hand, OpenShift provides the following key features:
- 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
"Easy to deploy" is the primary reason why developers consider Google App Engine over the competitors, whereas "Good free plan" was stated as the key factor in picking OpenShift.
OpenShift is an open source tool with 916 GitHub stars and 562 GitHub forks. Here's a link to OpenShift's open source repository on GitHub.
Best Buy, Feedly, and Rovio are some of the popular companies that use Google App Engine, whereas OpenShift is used by Cloud9 IDE, Codecraft Solutions, and Jollydays. Google App Engine has a broader approval, being mentioned in 473 company stacks & 329 developers stacks; compared to OpenShift, which is listed in 48 company stacks and 52 developer stacks.
What is Google App Engine?
What is OpenShift?
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Heroku vs OpenShift. I've never decided which one is better. Heroku is easier to configure. Openshift provide a better machine for free. Heroku has many addons for free. I've chosen Heroku because of easy initial set-up. I had deployment based on git push. I also tried direct deployment of jar file. Currently Heroku runs my Docker image. Heroku has very good documentation like for beginners. So if you want to start with something, let's follow Heroku. On the other hand OpenShift seems like a PRO tool supported by @RedHat.
With Cloud Endpoints you can create and deploy mobile backend in one hour or less. And it is free (until you need extra scale). I would not recommend to use Java - python is faster and has all new appengine features.
Pros: everything is in one place: task queue, cron, backend instances for data processing, datastore, mapreduce. Cons: you cannot easily move your code from GAE. Even with special 3rd party services.
I needed a PaaS provider that didn't drop all the time and it's hard to find a good option for PHP applications. Openshift takes care of it. They are a little behind on PHP versions, but that can be solved with a custom cartridge. It requires a little more elbow grease to get rolling when you want to implement something they don't already have, but their quickstarts are great to get rolling with the basics quickly.
With Cloud Endpoints you can create and deploy mobile backend in one hour or less.
PaaS for back-end components, including external data ingestion APIs, front-end web service APIs, hosting of static front-end application assets, back-end data processing pipeline microservices, APIs to storage infrastructure (Cloud SQL and Memcached), and data processing pipeline task queues and cron jobs. Task queue fan-out and auto-scaling of back-end microservice instances provide parallelism for high velocity data processing.
checking a swap require a lot of cpu resource, roster normally come out same day of month, every month, at a particular time. Which make very high spike, our flag ship product, iSwap, with the capability looking swap possibility with 10000 other rosters base on user critieria, you need a cloud computing give you this magnitude of computing power. gae did it nicely, user friendly, easy to you, low cost.
SG-TravelBuddy server application is hosted on Red Hat OpenShift Online (v3). SG-TravelBuddy mobile (Android) app is connecting to this server for data operations.
App engine fills in the gaps in the increasingly smaller case where it's necessary for us to run our own APIs.
Very easy to make cloud computing of ML models , and use containers like Kubernetes.
Cloud instances to run our app, Cloud MySQL , Network Load Balancer