For the database scalability section, there a few important scenarios to focus on and I’ll start with SQL elastic pools, you know, what are they?
They’re ideal when you managing multiple SQL databases and you have unpredictable performance requirements within them.
Next, study horizontal scaling, especially sharding, keep in mind that this is the go-to solution when you need to distribute parts of your database across different regions, often for compliance or data residency type requirements that you have out there.
Another key area to study is the database integration across multiple databases. If you’re working with tools like Power BI, Excel, Tableau, you will need to pull data from many different sources into a single report. So, understanding how that works is going to be important; practice that in your lab. You know, keep in mind these features will allow you to query across multiple databases as if they were one, and don’t forget cost; cost plays a big role in choosing your scaling strategy.
Be prepared to evaluate tradeoffs between performance, complexity, and budget when looking at various scenarios within your test for these topics there.
The following table identifies key points to remember before choosing Vertical/Horizontal scaling.
| Requirement | Solution |
| Do you have to manage and scale multiple Azure SQL databases that have varying and unpredictable resource requirements? | SQL elastic pools. |
| Do you have different sections of the database residing in different parts of the world for compliance concerns? | Horizontal scaling by Sharding works best. |
| Are there dependencies, such as commercial BI or data integration tools where multiple databases contribute rows into a single overall result for use in Excel, Power BI, Tableau, or Cognos? | Use Elastic database tools and elastic query feature within it to access data spread across multiple databases. |
Consider cost together with your scaling strategy to find an optimal solution.