DP-900 Practice Question: Identify considerations for relational data on Azure
A company has multiple independent databases for different business units, each with low to moderate usage and varying workload patterns. They want to consolidate these databases into a single Azure SQL Database deployment option to share resources and reduce costs, while ensuring that databases do not starve each other of resources. Which Azure SQL Database deployment option should they choose?
⚠ Common exam trap
Test-takers frequently choose Single database (DTU model) thinking it is the simplest option, but they overlook the cost and resource-sharing benefits of elastic pools for consolidating multiple low-usage databases with varying workloads.
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
✓
Elastic pool
Elastic pools are designed for exactly this scenario: multiple databases with low to moderate usage and varying workload patterns. They allow databases to share a fixed pool of resources (eDTUs or vCores) while using built-in resource governance to prevent any single database from starving others, thus optimizing cost and performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Elastic pool
Why this is correct
An elastic pool is a collection of shared resources (eDTUs or vCores) on a single logical SQL Database server, with the pool's total compute and storage billed once rather than per database. Each business-unit database consumes from the shared pool only when active, so peaks in one unit don't require over-provisioning every database. For multiple independent databases with intermittent usage, this gives predictable aggregate cost and allows per-database min/max resource caps; therefore it is the correct choice here.
- ✗
Single database (DTU model)
Why it's wrong here
A single database in the DTU model is provisioned with its own isolated DTU allocation and is billed at that full fixed tier even when it is idle. Keeping each business unit as its own single database would require choosing a DTU/performance tier for every database independently, and those separate reservations cannot be shared among units. With several independently scalable databases, this typically results in wasted capacity and higher total cost, so it is not the best fit for this scenario.
- ✗
Managed Instance
Why it's wrong here
Azure SQL Managed Instance delivers near 100% SQL Server engine compatibility, isolated VNet placement, and dedicated compute/storage, making it a lift-and-shift target for existing SQL Server workloads rather than a multi-database pooling service. You cannot place multiple business-unit databases into a single elastic pool inside a Managed Instance; each instance is independently sized and typically hosts SQL Agent jobs, cross-database queries, and instance-level features. Though it can host many databases, its pricing and governance model are tied to a dedicated instance, so it does not provide the shared, elastic per-database resource allocation this scenario needs.
- ✗
Database per server (hyperscale)
Why it's wrong here
Hyperscale is an architecture within Azure SQL Database for a single heavily-scaled database, separating compute, storage, and log so a database can scale to many TB with fast provisioning. Calling this option 'database per server (hyperscale)' is misleading because it still amounts to one independently managed database, not a shared pool; each business unit would get its own isolated hyperscale capacity and be billed separately. It is designed for extreme OLTP scale and availability on one database, not for pooling the resource demands of several small, variable business units.
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