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Apache Camel
Apache Camel

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Google App Engine
Google App Engine

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Apache Camel vs Google App Engine: What are the differences?

Developers describe Apache Camel as "A versatile open source integration framework". An open source Java framework that focuses on making integration easier and more accessible to developers. On the other hand, Google App Engine is detailed 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.

Apache Camel belongs to "Integration Tools" category of the tech stack, while Google App Engine can be primarily classified under "Platform as a Service".

According to the StackShare community, Google App Engine has a broader approval, being mentioned in 482 company stacks & 345 developers stacks; compared to Apache Camel, which is listed in 14 company stacks and 9 developer stacks.

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What is Apache Camel?

An open source Java framework that focuses on making integration easier and more accessible to developers.

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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Why do developers choose Apache Camel?
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      What tools integrate with Apache Camel?
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      What are some alternatives to Apache Camel and Google App Engine?
      Kafka
      Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
      ActiveMQ
      Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.
      Apache NiFi
      An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
      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.
      AWS Elastic Beanstalk
      Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.
      See all alternatives
      Decisions about Apache Camel and Google App Engine
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      Reviews of Apache Camel and Google App Engine
      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 Apache Camel and Google App Engine
      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

      How much does Apache Camel cost?
      How much does Google App Engine cost?
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