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 company stores user session data. Each session record must be quickly looked up by user ID and must have strong consistency so that once a session is written, subsequent reads always return the latest data. The company expects billions of session records globally and needs low-latency reads/writes. Which Azure data store best meets these requirements?
⚠ Common exam trap
A common mix-up: candidates confuse Azure Table Storage's low cost and key-value model with the strong consistency requirement, not realizing that Table Storage defaults to eventual consistency and cannot guarantee that a read immediately after a write returns the latest data, especially in globally distributed scenarios.
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 (SQL API)
Azure Cosmos DB with SQL API is the correct choice because it offers single-digit millisecond read/write latencies at any scale, global distribution, and tunable consistency levels including strong consistency. Strong consistency ensures that once a write is acknowledged, all subsequent reads return the latest data, which is critical for session state where stale reads could cause authentication or authorization failures. Cosmos DB also supports automatic indexing and partitioning by user ID, enabling fast lookups across billions of records.
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 (SQL API)
Why this is correct
Correct. Azure Cosmos DB with the SQL API is a schema-agnostic, multi-model database that offers single-digit-millisecond point reads by session ID, turnkey global distribution, and five consistency levels ranging from eventual to strong. Session records are naturally modeled as JSON documents keyed by session ID, and the SQL API supports SQL querying over those documents while maintaining a 99.999% availability SLA. This combination of low-latency point lookups, global reads/writes, and tunable strong consistency is exactly what a social media session store requires.
- ✗
Azure Blob Storage
Why it's wrong here
Incorrect. Azure Blob Storage is optimized for storing massive unstructured objects such as video files, images, and backups, not for performing frequent, low-latency point lookups of tiny session records. Each session would require a separate blob and an HTTP GET/PUT per request, which is far less efficient than the indexed document reads Cosmos DB provides. While blob storage is durable and strongly consistent, its access pattern and cost model are designed for streaming/sequential access rather than high-rate key-value lookups.
- ✗
Azure Table Storage
Why it's wrong here
Incorrect. Azure Table Storage is a key-value store that can hold session records, but it is a single-region service with no turnkey global distribution and no configurable consistency levels; you get only the service's default strong consistency within a partition, not the choice of eventual or bounded staleness for globally replicated data. Managing global distribution with Table Storage would require complex custom replication or traffic manager setups, whereas Cosmos DB provides multi-region writes and automatic failover out of the box. For a social media company with users distributed worldwide, that operational gap rules out Table Storage.
- ✗
Azure Cache for Redis
Why it's wrong here
Incorrect. Azure Cache for Redis is an in-memory cache, not a durable database; it keeps data in memory and can lose data on eviction or failover, so it cannot serve as the authoritative session store for a social media company. It is often used to accelerate reads by caching hot sessions in front of a persistent store like Cosmos DB, but it lacks the durability, transactional guarantees, and multi-region data residency needed for a source-of-truth session layer. Relying solely on Redis for session data would risk losing user sessions during a cache restart.
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Related to this question
Learn chapter
Data Roles and Core Concepts
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.
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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