Comparing costs between public cloud providers


I am often discussing the different platforms with people and we often end up discussing the different prices. People keep on asking me how much money you have to invest for a specific number of instances. It is necessary to look up different websites and so on. I came up with the idea of creating a simple cost comparison calculator with javascript on my blog. And I can now say: here it is!

Click here to go to the Calculator.

The cost comparision calculator gives you 3 different options:

  • Calculate the best price for cpu intense applications
  • Calculate the best price for memory intense applications
  • Calculate the best cheapest instances available.

The cost comparison calculator currently compares the following platforms:

  • Amazon EC2
  • Google Compute Engine
  • Rackspace Cloud Servers
  • Windows Azure Virtual Machines

A challenge is, what to compare. Each vendor has different instance types, so a comparison is often not so easy. Therefore, I have decided to split the comparison into different challenges as described above. For the first calculation – with cpu intense applications – i’ve used the lowest available instance. Basically, all 4 instance types matched despite Google. Google offers less memory than the other instances. The cheapest instances targets targets micro instances. All vendors despite Google offers micro instances. The memory comparison targets high memory instances.  The calculation is based on available memory. The memory is aligned to the number of instances necessary. For instance, if we select 68 GB of RAM, we need one instance at Amazon EC2 but multiple instances with Windows Azure. The prices are not aligned to instances but to the sum of memory. This leads to cheaper prices when using EC2 for lower memory. I will try to adjust this in the future.

To get updates on the calculator, you can subscribe to the newsletter below.

 

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Click here to go to the Calculator.

 

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Published by

Mario Meir-Huber

I work as Big Data Architect for Microsoft. With this role, I support my customers in applying Big Data technologies - mainly Hadoop/Spark - for their use-cases. I also teach this topic at various universities and frequently speak at various Conferences. In 2010 I wrote a book about Cloud Computing, which is often used at German & Austrian Universities. In my home country (Austria) I am part of several organisations on Big Data.

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