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 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?
⚠ Common exam trap
Many candidates 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.
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.
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.
- ✗
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.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data Lake Storage Gen2
Data Lake Storage Gen2 is a cloud-based storage service that combines a scalable data lake with enterprise-grade file system capabilities for big data analytics.
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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