Describe considerations for working with non-relational data on Azure →easyMultiple ChoiceObjective-mapped
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
A retail company plans to store product catalog data that includes product ID, name, description, price, and a varying set of attributes (e.g., size, color, material). The application requires low-latency reads and writes, global distribution, and the ability to handle schema flexibility. Which Azure data store is best suited for this workload?
⚠ Common exam trap
Many candidates confuse Azure Table Storage with Cosmos DB because both are NoSQL, but Table Storage lacks global distribution with multi-region writes and the low-latency guarantees required for this workload, while Cosmos DB is the only option that combines schema flexibility, global distribution, and low-latency reads/writes.
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 best choice because it provides low-latency reads and writes (single-digit milliseconds at the 99th percentile), global distribution with multi-region writes, and automatic schema flexibility through its document model. It supports varying product attributes (e.g., size, color, material) without requiring schema changes, and its turnkey global distribution ensures data is replicated across regions for fast access.
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 SQL Database
Why it's wrong here
Azure SQL Database is a relational database engine built on a fixed tabular schema with enforced primary/foreign keys, data types, and constraints. Product catalogs often contain products with highly variable attributes, so forcing those into columns or using EAV (entity-attribute-value) patterns would require complex joins and frequent ALTER TABLE statements. While SQL Database offers powerful querying and ACID transactions, it is not the most natural or cost-effective fit for rapidly evolving, heterogeneous product data.
When this WOULD be correct
A question where the workload requires complex relational queries, ACID transactions, and a fixed schema, such as an order management system with strict data integrity and reporting needs.
- ✓
Azure Cosmos DB
Why this is correct
Azure Cosmos DB is the correct choice because it is a multi-model NoSQL database service that natively supports document, key-value, graph, and column-family data models. Its schema-agnostic nature allows each product to have a different set of attributes (e.g., a shirt has size/color, a laptop has RAM/CPU) without requiring migrations or null placeholders. Cosmos DB also provides single-digit-millisecond read/write latency, automatic indexing, and turnkey global distribution, which are essential for a retail product catalog that must be fast and available across regions.
- ✗
Azure Table Storage
Why it's wrong here
Azure Table Storage is a NoSQL key-value store that stores entities as partitioned rows of property-value pairs, but it is not a document database. It lacks the ability to nest complex objects (e.g., arrays of variant SKUs or JSON subdocuments) and its querying is limited to partition key/row key lookups or filtered scans, with no secondary indexes or aggregate functions. A product catalog often needs to query by arbitrary attributes like brand or price range, which Table Storage handles poorly.
When this WOULD be correct
A scenario requiring cost-effective storage for large volumes of structured non-relational data (e.g., IoT telemetry, log entries) with simple key-based lookups and no need for global distribution or complex queries.
- ✗
Azure Blob Storage
Why it's wrong here
Azure Blob Storage is an object storage service designed for massive amounts of unstructured binary data, such as images, videos, logs, and backups. Because blobs are stored as opaque binary streams, you cannot run SQL-like queries, update individual fields without rewriting the whole blob, or enforce relationships between products. Using Blob Storage for a product catalog would force you to load entire JSON files into memory and filter in application code, making it unsuitable for interactive catalog queries.
When this WOULD be correct
A company needs to store large volumes of unstructured data such as product images, videos, or backup files, with no requirement for low-latency reads/writes on individual items or schema flexibility. The workload is primarily blob storage with infrequent access.
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 the correct choice because it is a multi-model NoSQL database service that natively supports document, key-value, graph, and column-family data models. Its schema-agnostic nature allows each product to have a different set of attributes (e.g., a shirt has size/color, a laptop has RAM/CPU) without requiring migrations or null placeholders. Cosmos DB also provides single-digit-millisecond read/write latency, automatic indexing, and turnkey global distribution, which are essential for a retail product catalog that must be fast and available across regions.
✗Azure SQL DatabaseWrong answer — click to see why▾
Why this is wrong here
Azure SQL Database enforces a fixed relational schema, which cannot handle the varying set of attributes (e.g., size, color, material) required for the product catalog. It also lacks native global distribution and low-latency multi-region writes.
★ When this WOULD be the correct answer
A question where the workload requires complex relational queries, ACID transactions, and a fixed schema, such as an order management system with strict data integrity and reporting needs.
Why candidates choose this
Candidates often associate product catalog data with relational databases, overlooking the schema flexibility and global distribution requirements that Azure Cosmos DB addresses.
✗Azure Table StorageWrong answer — click to see why▾
Why this is wrong here
Azure Table Storage lacks native global distribution and low-latency SLA guarantees across multiple regions, and its query capabilities are limited to partition and row keys, making it unsuitable for flexible schema queries on varying attributes.
★ When this WOULD be the correct answer
A scenario requiring cost-effective storage for large volumes of structured non-relational data (e.g., IoT telemetry, log entries) with simple key-based lookups and no need for global distribution or complex queries.
Why candidates choose this
Candidates may confuse Azure Table Storage's schema flexibility (entity property sets) with Cosmos DB's, overlooking its lack of global distribution and low-latency guarantees.
✗Azure Blob StorageWrong answer — click to see why▾
Why this is wrong here
Azure Blob Storage is optimized for unstructured binary data (e.g., images, videos, backups) and does not provide native support for schema-flexible JSON documents, low-latency queries on individual items, or global distribution with multi-region writes.
★ When this WOULD be the correct answer
A company needs to store large volumes of unstructured data such as product images, videos, or backup files, with no requirement for low-latency reads/writes on individual items or schema flexibility. The workload is primarily blob storage with infrequent access.
Why candidates choose this
Candidates may think Blob Storage can handle any type of data because it stores files, and they might overlook the need for low-latency queries and global distribution that Cosmos DB provides.
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
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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.
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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.