Azure Websites vs. Convox vs. Stackato

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Azure Websites

Convox

Stackato

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15

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Description

What is Azure Websites?

Azure Websites is a fully managed Platform-as-a-Service (PaaS) that enables you to build, deploy and scale enterprise-grade web Apps in seconds. Focus on your application code, and let Azure take care of the infrastructure to scale and securely run it for you.

What is Convox?

Convox is an open source Platform as a Service that runs in your own Amazon Web Services (AWS) account. Instead of signing up for a multi-tenant PaaS like Heroku, you can have your own. This gives you privacy and control over your platform and avoids the substantial markup on AWS prices that other platforms charge.

What is Stackato?

Stackato runs on top of your cloud infrastructure, and is the middleware from which your applications are launched. Developers simply upload their application source files to Stackato via IDE or command-line. Stackato automatically configures the required language runtimes, web frameworks, and data and messaging services.

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Why do you like Azure Websites?

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Why do you like Convox?

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Why do you like Stackato?

Cta desktop@2x

Pricing

Companies

67 Companies Using Azure Websites
7 Companies Using Convox
2 Companies Using Stackato

Integrations

Azure Websites Integrations
Convox Integrations
Stackato Integrations

What are some alternatives to Azure Websites, Convox, and Stackato?

  • Heroku - Build, deliver, monitor and scale web apps and APIs with a trail blazing developer experience.
  • Google App Engine - Build web applications on the same scalable systems that power Google applications
  • AWS Elastic Beanstalk - Quickly deploy and manage applications in the AWS cloud.
  • OpenShift - Red Hat's free Platform as a Service (PaaS) for hosting Java, PHP, Ruby, Python, Node.js, and Perl apps.

See all alternatives to Azure Websites

Latest News

The Convox 2.0 Development Platform
ALB Is Ready
eu-west-2 now supported by Convox
Helping Enterprises Keep up With Coder Innovation
Shifting Security Left, into the Application
How to Deploy Machine Learning Models to a .NET Envi...


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