Google App Engine vs. AppHarbor vs. Catalyze
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Google App Engine |
AppHarbor |
Catalyze |
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Favorites77
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Favorites5
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Favorites2
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Hacker News, Reddit, Stack Overflow Stats |
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Description |
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 AppHarbor?AppHarbor is a fully hosted .NET Platform as a Service. AppHarbor can deploy and scale any standard .NET application to the cloud.
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What is Catalyze?Cloud tools for healthcare. We provide a HIPAA-compliant Platform as a Service (PaaS), HIPAA-compliant Mobile Backend (BaaS), and HL7 integration services. Focus on building your digital health app, and not on compliance. Think of us as your healthcare-specific DevOps team.
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Pros about this tool |
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Pricing |
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Companies |
376 Companies Using Google App Engine
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2 Companies Using AppHarbor
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2 Companies Using Catalyze
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Integrations |
Google App Engine
Integrations
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AppHarbor
Integrations
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No integrations listed yet
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Latest News |
Cloud TPU machine learning accelerators now availabl...
February 12, 2018
Applying the Escalation Policy — CRE life lessons
February 08, 2018
GCP is building its second Japanese region in Osaka
February 07, 2018
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Reviews of Google App Engine, AppHarbor, and Catalyze
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.
Developer Friendly and Ideal for Startups
July 31, 2015 02:54
AppHarbor is an amazing tool for indie developers or startups that are just getting on their feet. To put it short, AppHarbor is the Heroku of .NET, being developer friendly, cost effective and performant.
Their platform has some nice features including the plugins (integrations with different services such as shared or dedicated RDBMS instances, document repositories, messaging queues, logging and monitoring services, etc.) that are extremely easy to use, and especially integrations with BitBucket and GitHub.
It's such a pleasure to work with the integrations mentioned, that whenever a developer pushes commits to the selected branch, AppHarbor automatically pulls, updates, builds, runs the unit tests and deploys. The cream of the crop is the fact that even the free tier supports this workflow which is practically a continuous delivery approach. And this makes AppHarbor perfect for startups and independent developers.
And, for established companies, I have to add the fact that their customer support is quite good.
How developers use Google App Engine vs AppHarbor vs Catalyze
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.
