DP-900 Practice Question: Identify considerations for relational data on Azure
A company runs an online booking system on Azure SQL Database. The system handles many concurrent transactions (OLTP). The business team runs complex reporting queries on the same database during business hours, which slows down the booking transactions. The company needs a solution to separate the analytical workload from the transactional workload without duplicating data manually. Which Azure SQL Database feature should they use?
⚠ Common exam trap
Watch out — candidates often confuse Active Geo-Replication (which also provides readable secondaries) with Read Scale-out, but Geo-Replication is regionally separated and intended for disaster recovery, not for local workload isolation within the same region.
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
✓
Read Scale-out (readable secondary replica)
Read Scale-out (readable secondary replica) is the correct choice because it allows the company to offload complex reporting queries to a read-only replica of the primary database, thereby isolating the analytical workload from the OLTP transactions. This feature is built into Azure SQL Database and does not require manual data duplication or ETL processes, directly addressing the requirement to separate workloads without manual effort.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Read Scale-out (readable secondary replica)
Why this is correct
Read Scale-out in Azure SQL Database leverages a built-in readable secondary replica in the same region. When a connection string specifies ApplicationIntent=ReadOnly, connections are automatically routed to that replica, allowing reporting and analytical queries to execute without consuming primary CPU and I/O. For an online booking system, this directly separates read-only load from transactional write traffic while maintaining the same logical database endpoint.
- ✗
Active Geo-Replication
Why it's wrong here
Active Geo-Replication copies data asynchronously to one or more secondaries in different regions, which is optimized for disaster recovery rather than operational workload separation. The asynchronous process introduces replication lag, so a secondary could return stale data if used for booking-related reads, and cross-region failover is overkill for merely offloading queries within one region. In-region read scaling is better handled by a synchronous read-only replica.
- ✗
Elastic pools
Why it's wrong here
Elastic pools are a resource governance model that lets multiple SQL databases share a fixed pool of DTUs or vCores, smoothing out utilization spikes and lowering cost. They do not create any additional replica for a database, nor do they alter how connections route on the primary server. Therefore, an elastic pool cannot separate read-only and read-write traffic within a single database.
- ✗
Hyperscale service tier
Why it's wrong here
The Hyperscale service tier is built for very large databases and near-instant scaling, but selecting that tier alone does not offload read queries—connections continue to target the primary replica. Hyperscale does support named replicas for read-only workloads, but that requires configuring the Read Scale-out feature with ApplicationIntent=ReadOnly, so it is the configuration, not the tier itself, that provides the separation. The question asks for the simplest feature, and standard Read Scale-out on Premium or Business Critical is more direct.
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
OLTP
OLTP (Online Transaction Processing) is a data processing system designed to manage and record high volumes of real-time transactions, such as bank deposits or online purchases, quickly and reliably.
Key term
Azure SQL Database
Azure SQL Database is a fully managed relational database-as-a-service (DBaaS) in Microsoft Azure, based on the SQL Server engine, that handles scaling, backups, patching, and high availability automatically.
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