AZ-305 Design data storage solutions Practice Question
A company is designing a data storage solution for a global e-commerce platform that requires low-latency access to product catalog data from multiple Azure regions. The data is read-heavy, with occasional updates. Which Azure data store should they recommend?
⚠ Common exam trap
It's easy for candidates to choose Azure Cache for Redis (Option A) because they associate low-latency with caching, but fail to recognize that the question requires a durable, globally distributed primary data store, not a cache layer that depends on an underlying database.
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 Cosmos DB
Azure Cosmos DB is the correct choice because it provides globally distributed, multi-region writes with tunable consistency levels and single-digit-millisecond latency for read-heavy workloads. Its ability to replicate data across Azure regions and serve reads from the nearest region directly addresses the requirement for low-latency global access to product catalog data with occasional updates.
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 Cache for Redis
Why it's wrong here
Azure Cache for Redis is an in-memory caching service that accelerates hot data access but does not provide durable, global data storage. Because it stores data in memory, evictions, node failures, or restarts cause permanent data loss, so it cannot be the system of record for a globally distributed application. Additionally, while Azure Cache for Redis can be clustered, it lacks native multi-region write replication and automatic failover for a primary data store across continents.
- ✗
Azure Blob Storage
Why it's wrong here
Azure Blob Storage is an object store for unstructured and large binary data, not a low-latency query engine for transactional workloads. Retrieving a specific record requires knowing its blob URL or listing and segmenting containers; there is no native secondary index or SQL-like query capability, so global applications cannot perform sub-10-millisecond point queries without adding external indexing. Blob tiering and eventual consistency across read-access geo-redundant storage also make it a poor fit for consistently fresh global reads.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database offers relational transactions, but without active geo-replication its single-region deployment introduces cross-continent network latency for remote users. Even with active geo-replication, readable secondaries are asynchronous and failover is not automatic for writes, so the database cannot accept writes in multiple regions simultaneously; a global write-master architecture would require custom sharding and failover logic. This makes Azure SQL Database a higher-complexity, higher-latency choice for a globally distributed low-latency data store.
- ✓
Azure Cosmos DB
Why this is correct
Azure Cosmos DB is a fully managed NoSQL database purpose-built for turnkey global distribution with multi-region writes and reads at single-digit millisecond latency. Each container can be mapped to multiple Azure regions, and data is replicated with multiple consistency models—from strong to eventual—giving developers predictable latency and availability trade-offs. With automatic failover and an SLA-backed 99.999% availability, Cosmos DB is the only option here engineered specifically as a distributed, low-latency, globally redundant data store.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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