Describe considerations for working with non-relational data on Azure →mediumMultiple ChoiceObjective-mapped
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
A social media startup needs to store user sessions as key-value pairs. Each session has a unique session ID, and the data needs to be globally distributed across multiple Azure regions to support low-latency reads for users worldwide. The development team expects heavy write throughput and needs flexible schema. Which Azure data store should they choose?
⚠ Common exam trap
Many exam-takers confuse Azure Cache for Redis (a caching layer) with a durable, globally distributed data store, overlooking that session data requiring persistence and global replication needs a database like Cosmos DB, not an in-memory cache.
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 and reads with turnkey global distribution, supports flexible schema via its document model, and offers multiple consistency levels to balance performance and data integrity. It is designed for high-throughput, low-latency workloads like user sessions, with session IDs serving as natural partition keys for efficient key-value lookups.
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 Table Storage
Why it's wrong here
Azure Table Storage is a NoSQL key-value service that stores entities as partitions, but its data placement is anchored to a single primary region (with optional asynchronous geo-redundant backup), not active-active multi-region writes. You also hit per-partition throughput ceilings around 20,000 operations per second and account-level scaling limits, which makes sustained heavy write workloads across geographically distributed users impractical. For session state that must be readable with low latency from any region, Table Storage's lack of native global distribution and strong consistency options makes it the wrong fit.
When this WOULD be correct
A question requiring a cost-effective, schema-less NoSQL store for structured data within a single Azure region, with moderate throughput and no global distribution needs.
- ✗
Azure Blob Storage
Why it's wrong here
Azure Blob Storage is an object store optimized for massive, unstructured binary payloads (large files, images, backups) rather than for tiny per-user session records requiring high-frequency point reads and updates. Blob storage uses a hierarchical namespace (container/blob) that lacks native query constructs to retrieve a single value by user ID, and its latency profile is designed for sequential streaming, not for millions of low-latency key-value lookups. While you could theoretically store serialized sessions in blobs, you would forfeit granular TTL, global active-active writes, and the throughput guarantee that a purpose-built key-value store provides.
When this WOULD be correct
A company needs to store and serve large media files (e.g., images, videos, backups) with high durability and availability, and can tolerate higher latency for reads. The data is accessed via URLs and does not require low-latency global distribution or flexible schema.
- ✓
Azure Cosmos DB
Why this is correct
Azure Cosmos DB is a fully managed NoSQL database that supports key-value stores via its Table API or Core (SQL) API, delivering single-digit-millisecond read/write latencies and turnkey global distribution across any number of Azure regions. Its multiple, well-defined consistency models — including the default Session consistency — align naturally with user-session data, where a user always reads their own writes. Because sessions benefit from automatic TTL expiration and elastic throughput, Cosmos DB is specifically architected for globally distributed, high-throughput key-value workloads rather than just tolerated as a secondary option.
- ✗
Azure Cache for Redis
Why it's wrong here
Azure Cache for Redis is fundamentally a caching layer: it holds data in memory for microsecond-to-low-millisecond access, but it does not guarantee durability by default, and even with Redis persistence (RDB/AOF) it is not engineered as a primary durable store with an enterprise-grade durability SLA. Global replication via Redis Geo-replication only mirrors across cache instances and still leaves the system vulnerable to data loss or failover gaps, while cache eviction policies like LRU can silently purge session entries. Session data that must survive restarts and be treated as authoritative storage therefore belongs in Cosmos DB, not Redis.
When this WOULD be correct
A question where the requirements are: low-latency reads for frequently accessed data, a caching layer to reduce database load, and data that can be stored in memory with optional persistence. For example: 'An e-commerce site needs to cache product details to reduce latency. Which service should they use?'
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The DP-900 exam frequently reuses these exact scenarios with slightly different constraints.
✓Azure Cosmos DBCorrect answer▾
Why this is correct
Azure Cosmos DB is a fully managed NoSQL database that supports key-value stores via its Table API or Core (SQL) API, delivering single-digit-millisecond read/write latencies and turnkey global distribution across any number of Azure regions. Its multiple, well-defined consistency models — including the default Session consistency — align naturally with user-session data, where a user always reads their own writes. Because sessions benefit from automatic TTL expiration and elastic throughput, Cosmos DB is specifically architected for globally distributed, high-throughput key-value workloads rather than just tolerated as a secondary option.
✗Azure Table StorageWrong answer — click to see why▾
Why this is wrong here
Azure Table Storage does not support global distribution with low-latency reads across multiple regions; it is regionally scoped and lacks multi-region write capabilities.
★ When this WOULD be the correct answer
A question requiring a cost-effective, schema-less NoSQL store for structured data within a single Azure region, with moderate throughput and no global distribution needs.
Why candidates choose this
Candidates may confuse Table Storage's key-value nature and schema flexibility with Cosmos DB, overlooking the critical requirement for global distribution and low-latency reads.
✗Azure Blob StorageWrong answer — click to see why▾
Why this is wrong here
Azure Blob Storage is optimized for storing large unstructured data like images and videos, not for high-throughput key-value sessions with low-latency global distribution and flexible schema.
★ When this WOULD be the correct answer
A company needs to store and serve large media files (e.g., images, videos, backups) with high durability and availability, and can tolerate higher latency for reads. The data is accessed via URLs and does not require low-latency global distribution or flexible schema.
Why candidates choose this
Candidates may confuse Blob Storage's key-value-like structure (container/blob) with a true key-value store, overlooking its lack of global distribution and low-latency guarantees for session data.
✗Azure Cache for RedisWrong answer — click to see why▾
Why this is wrong here
Azure Cache for Redis is an in-memory cache, not a fully managed NoSQL database. It lacks global distribution across multiple Azure regions and does not provide flexible schema for high write throughput scenarios like user sessions.
★ When this WOULD be the correct answer
A question where the requirements are: low-latency reads for frequently accessed data, a caching layer to reduce database load, and data that can be stored in memory with optional persistence. For example: 'An e-commerce site needs to cache product details to reduce latency. Which service should they use?'
Why candidates choose this
Candidates may think Redis is suitable because it supports key-value pairs and low-latency reads, but they overlook that it is primarily a cache, not a globally distributed database with flexible schema and high write throughput.
Analysis generated from the official DP-900blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Schema
A schema is a blueprint or logical structure that defines how data is organized, stored, and accessed in a database or information system.
Key term
Azure Cosmos DB
Azure Cosmos DB is a fully managed, globally distributed NoSQL database service that offers fast reads and writes anywhere in the world with automatic scaling and multiple consistency models.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-900 exam.