DP-900 Practice Question: Identify considerations for relational data on Azure
A multinational corporation is deploying a global application using Azure SQL Database. They need to ensure that users in different geographic regions experience low latency reads. The application can tolerate slightly stale data for reads, but writes must be strongly consistent and must occur in a single primary region. Which feature should they implement?
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
✓
Active geo-replication
Active geo-replication (Option B) creates readable secondary databases in other Azure regions. Reads can be directed to the secondary for low latency, while writes always go to the primary and are strongly consistent. This matches the requirement for globally distributed users with low-latency reads and strong consistency for writes. Option A (Azure Cosmos DB with multi-master) is a NoSQL solution, not relational. Option C (Failover groups) manages geo-replication and provides automatic failover, but it still relies on active geo-replication to create the readable secondaries; it does not directly enable low-latency reads. Option D (Read scale-out) uses local read-only replicas within the same region, not globally.
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 Cosmos DB with multi-master
Why it's wrong here
Azure Cosmos DB with multi-master is a NoSQL solution, not a relational database, so it doesn't align with the likely SQL-based transactional workload. Multi-master enables write operations in multiple regions, which introduces complexity around conflict resolution and is overkill if the requirement is simply to improve read latency. It also does not provide the same asynchronous readable secondary pattern as active geo-replication, and the write capability across regions is not desired in this scenario.
- ✓
Active geo-replication
Why this is correct
Active geo-replication is the correct choice because it creates readable secondary replicas of an Azure SQL database in different regions, allowing applications to direct read-only queries to the nearest secondary for low-latency access. These secondaries are maintained through asynchronous replication, so they are near-real-time but not guaranteed to be transaction-consistent with the primary. This directly addresses the need for global read performance while keeping the primary as the sole write endpoint, which is simpler and more predictable than multi-master.
- ✗
Failover groups
Why it's wrong here
Failover groups are designed primarily for high availability and disaster recovery, not for distributing read traffic across regions. While a failover group can include a readable secondary, its main function is to automate failover of the entire database (and server) to a secondary region during an outage, redirecting all connections to the new primary. It does not provide multiple readable secondaries for load balancing read requests, so it would not effectively minimize latency for users in many different regions.
- ✗
Read scale-out
Why it's wrong here
Read scale-out in Azure SQL Database uses built-in read-only replicas that reside in the same region as the primary database. These local replicas help offload reporting and analytics workloads from the primary, but they do not reduce latency for users in other geographic areas because the replicas are not distributed globally. Since the requirement is for low-latency reads across a multinational deployment, read scale-out is insufficient; active geo-replication is needed to place readable copies in multiple regions worldwide.
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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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