Azure SQL DW Reference Architectures

James Serra shows how Azure SQL Data Warehouse can fit into various warehousing architectures:

Do staging, data refinement and reporting all from SQL DW.  You can scale compute power up when needed (i.e. during staging, data refinement, or large number of users doing reporting) or down to save costs (i.e. nights and weekends when user reporting is low).  The pros of this option are by reducing the number of technologies you are building a simpler solution and reducing the number of copies of the data.  The cons are since everything is done on SQL DW you can have performance issues (i.e. doing data refinement while users are reporting), can hit the SQL DW concurrent query limit, and can have a higher cost since SQL DW is the highest-cost product, especially if you are not able to pause it.  Pausing it reduces your cost to zero for compute, only having to pay for storage (see Azure SQL Data Warehouse pricing), but no one can use SQL DW when paused

Click through for three other architecture ideas.

Related Posts

Automatic Processing Of Azure Analysis Services Models

Dustin Ryan shows how to use Azure Functions to refresh Azure Analysis Services models: Download the latest client libraries for Analysis Services. This needs to be done on your local machine so you can then copy these files to your Azure Function App. After you’ve downloaded the client libraries, the DLLs can be found in […]

Read More

Scripting Azure Resources With ARM Templates

Melissa Coates has a detailed explanation of how to script out the creation and configuration of services in Azure using Azure Resource Manager (ARM) templates: In many cases, you can easily provision resources in the web-based Azure portal. If you’re never going to repeat the deployment process, then by all means use the interface in […]

Read More

Categories