DP-900 Practice Question: Identify considerations for relational data on Azure
A company runs individual Azure SQL Databases for each of its departments. The databases experience varying usage patterns; sometimes one database is idle while another is heavily loaded. The company wants to pool resources to reduce cost while ensuring each database gets resources when needed. Which Azure feature should they use?
⚠ Common exam trap
The trap here is that candidates might confuse elastic pools with single databases or managed instances, thinking that 'pooling' means using a single large instance rather than a shared resource model across multiple databases.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure SQL Database elastic pool
Azure SQL Database elastic pools are designed to share resources (eDTUs or eVCores) across multiple databases with varying usage patterns. This allows idle databases to contribute their unused capacity to heavily loaded ones, reducing overall cost while ensuring each database gets resources when needed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure SQL Database single database with provisioned DTUs
Why it's wrong here
A single database with provisioned DTUs allocates a fixed, isolated set of compute, storage, and I/O resources to each database. Because these resources are not shared, you must size each database for its peak workload, and you continue paying for that full allocation even when the database is idle. With many databases, this typically results in significant over-provisioning and higher aggregate cost compared to a pooled model.
- ✓
Azure SQL Database elastic pool
Why this is correct
An elastic pool lets multiple Azure SQL databases share a common pool of eDTUs (or vCores), with each database assigned a minimum and maximum DTU limit. Databases that are idle automatically release resources for those under load, so the pool's total capacity can be far less than the sum of individual peak requirements. This makes it the most cost-efficient and operationally simple choice for a large number of databases with fluctuating usage, such as in a multi-tenant SaaS scenario.
- ✗
Azure SQL Managed Instance
Why it's wrong here
Azure SQL Managed Instance provides a fully managed SQL Server instance with instance-scoped features like linked servers and SQL Agent, but it does not support elastic pools. All databases hosted on a managed instance share the instance's fixed resource allocation, and you cannot dynamically rebalance resources among databases independently of the instance. Because you pay for the entire instance's capacity, running many small databases with intermittent workloads often leads to underutilization and higher costs than an elastic pool.
- ✗
SQL Server on Azure Virtual Machines
Why it's wrong here
SQL Server on Azure Virtual Machines offers IaaS-level control, but you must manually manage the VM, SQL Server licensing, patching, and high availability. There is no built-in pooled resource model; while you could host multiple databases on one VM, the databases compete for the VM's static CPU and memory, and you cannot easily scale or reallocate resources per database without downtime or manual configuration. This approach is operationally heavy and generally more expensive than PaaS elastic pools for a large fleet of small, spiky databases.
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