DP-900 Practice Question: Identify considerations for relational data on Azure
A SaaS provider hosts databases for hundreds of clients, each with light and sporadic usage. They notice that using separate single databases with provisioned DTUs is cost-inefficient. They need to consolidate the databases while optimizing cost and ensuring that a busy client does not monopolize resources. Which Azure SQL Database option should they use?
⚠ Common exam trap
A common mix-up: candidates confuse elastic pools with single databases, thinking that provisioned DTUs are always cheaper for sporadic workloads, but they miss that elastic pools share resources across databases to eliminate over-provisioning waste.
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
An Azure SQL Database elastic pool is designed to optimize cost for multiple databases with light and sporadic usage by sharing a fixed set of resources (eDTUs) across all databases in the pool. This prevents a busy client from monopolizing resources through per-database resource limits (min and max DTU), ensuring performance isolation while consolidating costs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Single database with provisioned DTU
Why it's wrong here
Provisioning DTUs per single database allocates a fixed, dedicated capacity to each tenant, so an idle database still consumes its full purchased DTUs while occasional spikes force you to buy extra headroom you rarely use. For hundreds of clients, this model leads to severe over-provisioning and high aggregate cost because the workload is only pooled at the billing level, not at the compute level, and no dynamic sharing occurs across databases.
- ✓
Elastic pool
Why this is correct
Elastic pools place multiple tenant databases into a single shared resource pool with per-database minimum and maximum DTU settings, so the pool's aggregate capacity absorbs each tenant's spikes while idle databases contribute unused capacity back to the pool. This matches the SaaS pattern of many small databases with low average usage: you pay for the pooled DTUs actually needed rather than a fixed amount per tenant, and the built-in performance isolation prevents one tenant from starving others.
- ✗
Managed Instance
Why it's wrong here
Azure SQL Managed Instance is a PaaS offering that provides near-100% SQL Server instance-level compatibility, including linked servers, CLR, and cross-database queries, but it allocates a dedicated vCore-based instance with its own storage and compute. For hundreds of small SaaS tenants, running a Managed Instance per tenant is prohibitively expensive and lacks the fine-grained, multi-tenant resource pooling that elastic pools provide, so it is better suited to migrating a few large legacy databases that need instance-wide features.
- ✗
SQL Server on Azure VM
Why it's wrong here
Installing SQL Server on an Azure VM leaves you responsible for patching the OS and SQL Server, managing high availability, and licensing, while the VM's size must be sized for peak load and you pay for the entire VM even when the database is idle. To support hundreds of clients you would either need hundreds of small VMs, which is operationally unmanageable, or one giant VM with manually consolidated databases, which loses the automatic resource collation and isolation that an elastic pool builds in.
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