- A
Azure Blob Storage (with Azure Data Lake Storage Gen2) and query using Azure Synapse Serverless SQL
Correct. This combination provides cost-effective storage and serverless SQL querying without infrastructure management.
- B
Azure Cosmos DB
Why wrong: Incorrect. Cosmos DB is designed for low-latency, high-throughput transactional workloads. Storing terabytes of rarely accessed JSON data in Cosmos DB would be expensive and does not leverage its key benefits.
- C
Azure Table Storage
Why wrong: Incorrect. Table Storage is a NoSQL key-value store that does not support SQL queries or JSON document storage directly.
- D
Azure SQL Database
Why wrong: Incorrect. SQL Database requires provisioning and managing compute resources (DTUs/vCores), which contradicts the requirement of not managing servers.
Quick Answer
The correct answer is Azure Blob Storage with Azure Data Lake Storage Gen2 for storage, queried via Azure Synapse Serverless SQL. This combination is ideal because Azure Synapse Serverless SQL allows analysts to run standard T-SQL queries directly against JSON files stored in blob storage without provisioning any servers or managing throughput, perfectly matching the requirement for a serverless, on-demand solution for rarely modified data. On the DP-900 exam, this scenario tests your understanding of when to choose serverless versus provisioned resources—a common trap is selecting Azure SQL Database or Synapse Dedicated SQL Pool, which require capacity management. Remember that if the question emphasizes “no server management” and “querying files in place,” Synapse Serverless SQL is the go-to service. A helpful memory tip: think of “Serverless SQL” as a query engine that reads files where they live, not a database that stores them.
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
This DP-900 practice question tests your understanding of describe considerations for working with non-relational data on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company stores terabytes of customer support chat transcripts in JSON format. The data is rarely modified and needs to be accessed by analysts using SQL queries. The analysts do not want to manage servers or provision throughput. Which Azure service should be used to store and query this data?
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 Blob Storage (with Azure Data Lake Storage Gen2) and query using Azure Synapse Serverless SQL
Azure Blob Storage with Azure Data Lake Storage Gen2 provides a cost-effective, scalable solution for storing large volumes of JSON data in its native format. By using Azure Synapse Serverless SQL, analysts can query this data directly with standard T-SQL without provisioning any infrastructure or managing throughput, meeting the requirement for serverless, on-demand querying of rarely modified data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 Blob Storage (with Azure Data Lake Storage Gen2) and query using Azure Synapse Serverless SQL
Why this is correct
Correct. This combination provides cost-effective storage and serverless SQL querying without infrastructure management.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Cosmos DB
Why it's wrong here
Incorrect. Cosmos DB is designed for low-latency, high-throughput transactional workloads. Storing terabytes of rarely accessed JSON data in Cosmos DB would be expensive and does not leverage its key benefits.
- ✗
Azure Table Storage
Why it's wrong here
Incorrect. Table Storage is a NoSQL key-value store that does not support SQL queries or JSON document storage directly.
- ✗
Azure SQL Database
Why it's wrong here
Incorrect. SQL Database requires provisioning and managing compute resources (DTUs/vCores), which contradicts the requirement of not managing servers.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Cosmos DB's SQL API with traditional SQL querying, overlooking the requirement to avoid provisioning throughput, or they assume Azure Table Storage supports SQL queries when it only supports key-value lookups via REST or OData.
Detailed technical explanation
How to think about this question
Azure Synapse Serverless SQL uses a distributed query engine that reads data directly from Azure Data Lake Storage Gen2 via the OPENROWSET function, leveraging columnar formats like Parquet or Delta Lake for efficient querying. Under the hood, it partitions the query across compute nodes and uses predicate pushdown to filter data at the storage layer, minimizing data movement. In real-world scenarios, this pattern is ideal for data lakes where JSON files are stored in a hierarchical namespace, allowing analysts to query terabytes of data with pay-per-query pricing without any infrastructure management.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe considerations for working with non-relational data on Azure — This question tests Describe considerations for working with non-relational data on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Blob Storage (with Azure Data Lake Storage Gen2) and query using Azure Synapse Serverless SQL — Azure Blob Storage with Azure Data Lake Storage Gen2 provides a cost-effective, scalable solution for storing large volumes of JSON data in its native format. By using Azure Synapse Serverless SQL, analysts can query this data directly with standard T-SQL without provisioning any infrastructure or managing throughput, meeting the requirement for serverless, on-demand querying of rarely modified data.
What should I do if I get this DP-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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.
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