Analysis Services in the Cloud: IaaS vs PaaS

When deciding to deploy an Analysis Services solution to the cloud, one of the very first decisions to make is whether to go with an Infrastructure-as-a-Service or Platform-as-a-Service architecture.

The diagram below does a good job in explaining the differences between the two.

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Note: from an Analysis Services cloud architecture perspective, the “Software-as-a-Service” is simply not an option offered by Microsoft. However, depending on your business model and product line, you might build & offer a Software-as-a-Service solution to your end customers based on Analysis Services IaaS or PaaS (and a good bit of other technology and custom code). In other words, Microsoft doesn’t offer it, but you could build it! If you’re interested, please reach out… I would love to work on a project like that.

The rest of this post provides a breakdown of the 2 options (IaaS vs PaaS) to help you make that decision.

Infrastructure as a Service (IaaS)

This option is basically the same as an on-premise virtualized environment (e.g. VMware, HyperV) only instead of owning the host servers, networking, storage solution, & virtualization layer… you lease all that stuff from Microsoft.


  • super easy migration path (i.e. “lift and shift”) for existing on-premise solutions
  • scaling up/down is easier than on-premise solutions (but not as easy or fast as PaaS)
  • not limited to Azure… can deploy to AWS and other cloud providers
  • can run Tabular and/or Multidimensional solutions
  • option to bring your own SQL Server license
  • lots of hardware (CPU/Memory/Disk) options to choose from (almost too many!)
  • ability to run SQL DB and SSAS side-by-side


  • difficult to scale-out for high-concurrency scenarios (same approach as on-premise)
  • difficult to grant access to public/external users (same as on-premise)
  • must design and implement HA/DR yourself
  • must apply software and security updates yourself


Platform as a Service (PaaS)

This is the SSAS-equivalent of Azure SQL DB… Azure AS. The main difference, is that Azure SQL DB is can be thought of as a “Database-as-a-Service” whereas Azure AS is more along the lines of an “Instance-as-a-Service”.


  • automagic software and security updates
  • automagic HA/DR
  • dynamic scale up/down
  • dynamic scale in/out
  • management API
  • easy to grant access to public/external users


  • migration path is a bit more involved than the IaaS (but not exactly difficult)
  • stuck w/ Azure (though that’s not really a bad thing these days)
  • no multidimensional option (yet?)
  • fewer options in terms of HW (CPU/Memory)


Cost is an important factor (perhaps the most important) but also one that’s very hard to calculate due to the wide variability in solution requirements and pricing breaks. The longer I spend in this industry, the more I realize that list-price is just a starting point for negotiations and only “direction-ally” useful.

However, if you’re interested, I’ve scraped the hourly pricing from the MSFT sites for Azure VMs and Azure AS instances and lined them up to help compare at the various break-points (download excel file).


Couple of points to keep in mind…

  • these are list prices… please don’t pay this amount before negotiating w/ your MSFT rep
  • Hardware performance is not necessarily apples-to-apples… clock-speed/cache of the CPUs behind Azure AS are still not publicly disclosed (as far as I’m aware)… same w/ memory frequency (much more is known and/or discoverable w/ Azure VMs).
  • prices are about the same at each level assuming you lease the Azure VMs w/ SQL license… if you already have your own SQL license, then you can just lease the Azure VM w/ windows (or linux) and pay quite a bit less.

Additional References:

4 replies on “Analysis Services in the Cloud: IaaS vs PaaS”

yes, to some extent that is true… e.g. custom content packs for third-party providers such as Google Analytics, SalesForce, Dynamics, etc

but I would argue the main scenario w/ PBI is more similar to the PaaS version where data modeling, calculations, and reporting are your responsibility.


Yea, you do have to develop your data model which would make it more like a PaaS. Good point! I guess I was thinking of the PowerBI itself. But, it does function more like Salesforce from that aspect.


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