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Google App Engine
Google App Engine

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jFrog
jFrog

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Google App Engine vs jFrog: What are the differences?

Google App Engine: 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; jFrog: Universal Artifact Management. Host, manage and proxy artifacts using the best Docker Registry, Maven Repository, Gradle repository, NuGet repository, Ruby repository, Debian repository npm repository, Yum repository.

Google App Engine and jFrog can be categorized as "Platform as a Service" tools.

According to the StackShare community, Google App Engine has a broader approval, being mentioned in 482 company stacks & 345 developers stacks; compared to jFrog, which is listed in 22 company stacks and 8 developer stacks.

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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.

What is jFrog?

Host, manage and proxy artifacts using the best Docker Registry, Maven Repository, Gradle repository, NuGet repository, Ruby repository, Debian repository npm repository, Yum repository.
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Why do developers choose Google App Engine?
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          What are some alternatives to Google App Engine and jFrog?
          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.
          Amazon Web Services
          It provides on-demand cloud computing platforms to individuals, companies and governments. It offers reliable, scalable, and inexpensive cloud computing services.
          DigitalOcean
          We take the complexities out of cloud hosting by offering blazing fast, on-demand SSD cloud servers, straightforward pricing, a simple API, and an easy-to-use control panel.
          AWS Lambda
          AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.
          Kubernetes
          Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.
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          Decisions about Google App Engine and jFrog
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          Reviews of Google App Engine and jFrog
          Review ofGoogle App EngineGoogle App Engine

          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.

          Review ofGoogle App EngineGoogle App Engine

          With Cloud Endpoints you can create and deploy mobile backend in one hour or less.

          How developers use Google App Engine and jFrog
          Avatar of Casey Smith
          Casey Smith uses Google App EngineGoogle 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.

          Avatar of Lawrence Cheuk
          Lawrence Cheuk uses Google App EngineGoogle 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.

          Avatar of CommentBox.io
          CommentBox.io uses Google App EngineGoogle App Engine

          App engine fills in the gaps in the increasingly smaller case where it's necessary for us to run our own APIs.

          Avatar of Abhijeet Gokar
          Abhijeet Gokar uses Google App EngineGoogle App Engine

          Very easy to make cloud computing of ML models , and use containers like Kubernetes.

          Avatar of Vamsi Krishna
          Vamsi Krishna uses Google App EngineGoogle App Engine

          Cloud instances to run our app, Cloud MySQL , Network Load Balancer

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