Heroku vs. Google App Engine vs. Paz
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Heroku |
Google App Engine |
Paz |
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Favorites294
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Favorites77
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GitHub Stats |
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Description |
What is 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.
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What is Google App Engine?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.
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What is Paz?A pluggable in-house service platform with a PaaS-like workflow, built on Docker, CoreOS, Etcd and Fleet.
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Pros about this tool |
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Pricing |
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Companies |
1356 Companies Using Heroku
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374 Companies Using Google App Engine
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0 Companies Using Paz
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Integrations |
Heroku
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Google App Engine
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Paz
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Latest News |
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January 17, 2018
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Cloud TPU machine learning accelerators now availabl...
February 12, 2018
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GCP is building its second Japanese region in Osaka
February 07, 2018
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Reviews of Heroku, Google App Engine, and Paz
Great way to get apps out there, easy to outgrow
February 04, 2014 11:12
Can't beat the simplicity of deploying and managing apps, the pricing is a bit high, but you are paying for those streamlined tools. However, after several experiences of tracing issues back to Heroku's stack, not having visibility into what they are doing has prompted moving two applications off of it and on to other more transparent cloud solutions. Heroku is amazing for what it is, hosting for early stage products.
Indispensable for prototyping
February 04, 2014 03:51
I've been using Heroku for 3 years now, they have grown super fast and each time they're improving their services. What I really like the most is how easily you can show to your client the advances on you project, it would take you maximum 15 minutes to configure two environments (Staging/Production). It is simply essential and fantastic!
Good servers to start out on
May 10, 2014 14:11
I use Heroku as a starting server for my app. Heroku is easy to use and isn't crashing on me all the time.
Heroku is for everyone
March 24, 2014 06:39
I use Heroku, for almost any project of mine. Their free plan is awesome for testing, solo developers or your startup and its almost impossible to not cover you somehow. Adding an add on is a simple command away and I find it easy to use it both on my Windows PC or my Linux laptop. Their documentation, covers almost everything. In particular I have used Heroku for Spring, Django and AngularJS. I even find it easier to run my project on my local dev with foreman start, than ./manage.py runserver (for my django projects). There is no place like Heroku for the developer!
Stress free PAAS
May 05, 2014 01:47
Using Heroku takes away all the pains associated with managing compute and backing services. It may require a little extra optimisation and tweaks, but these constraints often make your app better anyway.
Easy to Use and Free to Get Started
April 06, 2016 08:39
I liked how easy this was to use and that I could create some proof of concepts without have to pay. The downside for NodeJS is remote debugging. Pretty much have to depend on logging where Azure allows remote debugging with Node Inspector.
Easily create scalable backend for mobile
March 27, 2014 07:50
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.
Easily create scalable backend for mobile
March 26, 2018 00:24
With Cloud Endpoints you can create and deploy mobile backend in one hour or less.
How developers use Heroku vs Google App Engine vs Paz
Mobtest uses Heroku
Our app is built using Ruby on Rails. We deploy on Heroku via github. We have separate instances for prod and staging, and can increase/decrease dyno's depending on load.
StackShare uses Heroku
We keep the Metrics tab open while we load test, and hit refresh to see what’s going on: 
I would expect the graphs to expand with some sort of detail, but that’s not the case. So these metrics aren’t very useful. The logs are far more useful, so we just keep the tail open while we test.
StackShare uses Heroku
Not having to deal with servers is a huge win for us. There are certainly trade-offs (having to wait if the platform is down as opposed to being able to fix the issue), but we’re happy being on Heroku right now. Being able to focus 100% of our technical efforts on application code is immensely helpful.
Two dynos seems to be the sweet spot for our application. We can handle traffic spikes and get pretty consistent performance otherwise.
We have a total of four apps on Heroku: Legacy Leanstack, StackShare Prod, StackShare Staging, StackShare Dev. Protip: if you’re setting up multiple environments based on your prod environment, just run heroku fork app name. Super useful, it copies over your db, add-ons, and settings.
We have a develop branch on GitHub that we push to dev to test out, then if everything is cool we push it to staging and eventually prod. Hotfixes of course go straight to staging and then prod usually.
danlangford uses Heroku
With its complimentary SSL (on *.herokuapp.com) we can test everything. Our dev branch is built and deployed out to Heroku. Testing happens out here. not production cause $20/mo is TOO much to pay for the ability to use my own SSL purchased elsewhere.
SmartLogic uses Heroku
Heroku is amazing. We use the effortless git integration to deploy code for review to our clients. We also have projects that run on Heroku in production.
rhnorment uses Heroku
5 years of experience using Heroku for application deployment, management, and production.
Spidy88 uses Heroku
Hosts the main Sweat Shop application as well as all worker applications (deployed on their own instances)
romaninsh uses Heroku
Agile Toolkit default project is configured for easy installation through Heroku.
toolmantim uses Heroku
Heroku runs the web and background worker processes. Auto-deployments are triggered via GitHub commits and wait for the Buildkite test build to pass. Heroku pipelines with beta release phase execution (for automatically running database migrations) allowed for easy manual testing of big new releases. Web and worker logs are sent to Papertrail.
ReviewTrackers uses Heroku
Most of our apps and services start life on heroku before moving upstream to AWS.
thibmaek uses Heroku
Main platform of deployment. This proved to be the easiest with our React + Node stack.
We had the develop branch deployed on a staging subdomain and master on the rootdomain.
SaberEsPoder uses Heroku
Our main apps are hosted on Heroku. We use Papertrail for logging, the Heroku Scheduler to automate rake tasks and deploy automatically through CircleCI.
papaver uses Heroku
used heroku on and off for many projects over the last 5 years. quick and dirty application infrastructure without the headaches. it ain't cheap up its worth the time savings.
jflynn33 uses Heroku
As much as I love AWS EC, I prefer Heroku for apps like this. Heroku has grown up around Rails and Ruby, massive set of add-ons that are usually one-click setup, and I once had to perform an emergency app scale-up a that I completed in seconds from my mobile phone whilst riding the Bangkok subway. Doesn't get much easier than that.
elabraha uses Heroku
MDST
We deployed an app for flint. It was cool I guess. I wasn't as apart of it as I should have been.
Virtually(Creative) uses Heroku
Documentation Hosting - easy to setup & free for small open source projects.
vamsiikrishna uses Google App Engine
Cloud instances to run our app, Cloud MySQL , Network Load Balancer
csmith932 uses Google App Engine
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.
shcheuk uses Google App Engine
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.
abunickabhi uses Google App Engine
Very easy to make cloud computing of ML models , and use containers like Kubernetes.
