Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A social media analytics company needs to store large amounts of user activity logs. Each log entry contains a timestamp, user ID, activity type, and a dynamic set of custom attributes (e.g., page viewed, time spent). The application requires low-latency writes and point reads by a composite key (user ID and timestamp). The data is rarely updated after insertion. The company wants a fully managed NoSQL database that supports serverless throughput and automatic expiration of old logs (TTL). Which Azure Cosmos DB API should they choose?
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.
A
Best answer
Table API
The Table API is built for key-value stores and supports a schema-less design with composite keys (PartitionKey + RowKey). It also supports serverless throughput and TTL (time-to-live) to automatically delete old entries, fitting the activity log use case.
B
Distractor review
NoSQL API (Core/SQL API)
The NoSQL API is for document data with flexible schemas and rich querying. While it supports TTL and serverless, it is more complex than needed for a simple key-value log. The Table API is more cost-effective and simpler for this exact pattern.
C
Distractor review
Cassandra API
The Cassandra API provides Cassandra-compatible column-family storage. It requires using the Cassandra Query Language (CQL) and is designed for wide-column workloads. It is overkill for simple key-value logs and does not natively support TTL via Cosmos DB settings (though Cassandra has TTL, integration can be less straightforward).
D
Distractor review
Gremlin API
The Gremlin API is for graph databases that model entities and relationships (edges). Activity logs are not inherently a graph structure, so this API is inappropriate for this use case.
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: Table API — The Azure Cosmos DB Table API is designed for key-value workloads and supports flexible schemas, serverless capacity mode, and TTL for automatic data expiration. The composite key can be formed using the PartitionKey (user ID) and RowKey (timestamp). This scenario fits the Table API perfectly. The NoSQL API (formerly DocumentDB) is also schema-agnostic but is more suitable for document-oriented data with rich queries and indexing. The Cassandra API is column-family based and requires a specific query language. The Gremlin API is for graph 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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