A company stores customer orders. Each order has a unique order ID, customer ID, a list of items (each item contains product ID, quantity, and price), and an order date. They frequently query orders by customer ID and also need to filter by order date ranges. The data volume is high and schema flexibility is desired because items can vary in structure. Which type of data store is best suited for this scenario?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
Distractor review
Relational database
Incorrect. While a relational database can represent this data, it would require separate tables and joins, increasing complexity. A document database is more natural for embedded items.
Distractor review
Key-value store
Incorrect. Key-value stores are optimized for simple lookups by key, not for querying on multiple fields like customer ID and date.
Best answer
Document database
Correct. Document databases store data in nested documents (e.g., JSON), which matches the order-with-items structure, and support indexing on multiple fields for flexible queries.
Distractor review
Graph database
Incorrect. Graph databases are meant for highly connected data (e.g., social networks), not for document-oriented transactional data.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Related practice questions
Related DP-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?
Question 2
A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?
Question 3
A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?
Question 4
A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?
Question 5
A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?
Question 6
A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?
FAQ
Questions learners often ask
What does this DP-900 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Document database — A document database (like Azure Cosmos DB with NoSQL API) allows storing hierarchical data such as an order with embedded items as a single document. It supports indexing on fields like customer ID and order date for efficient queries, and provides flexible schemas. A relational database could also work but would require normalization (separate Orders and OrderItems tables) and more complex queries. A key-value store is not ideal because it does not support querying on multiple attributes efficiently. A graph database is designed for relationships between entities, not for this kind of transactional data.
What should I do if I get this DP-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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