- A
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
NoSQL API (Core/SQL API)
Why wrong: 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
Cassandra API
Why wrong: 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
Gremlin API
Why wrong: 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.
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 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
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Table API
The Table API is the correct choice because it provides a fully managed, serverless NoSQL database with automatic TTL (Time-to-Live) for data expiration, low-latency point reads and writes by a composite key (partition key + row key), and is optimized for storing large volumes of structured log data with dynamic attributes. It supports the exact requirements: high-throughput writes, point queries by user ID and timestamp, and automatic expiration of old logs without manual intervention.
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.
- ✓
Table API
Why this is correct
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
NoSQL API (Core/SQL API)
Why it's wrong here
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.
- ✗
Cassandra API
Why it's wrong here
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).
- ✗
Gremlin API
Why it's wrong here
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 traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose the NoSQL API (Core/SQL API) because it is the most well-known Cosmos DB API, but they overlook that the Table API is specifically optimized for high-volume, low-latency key-value workloads with composite keys and automatic TTL, making it the correct choice for log data with dynamic attributes.
Detailed technical explanation
How to think about this question
Under the hood, Azure Cosmos DB Table API uses a schema-less key-value store where the partition key (user ID) and row key (timestamp) form a unique composite key, enabling O(1) point reads and writes. The TTL feature is implemented at the item level, where each log entry can have a 'ttl' property (in seconds) that automatically deletes the item after expiration, reducing storage costs and eliminating the need for manual cleanup. In real-world scenarios, this is ideal for IoT telemetry or clickstream analytics where logs must be retained for a fixed period (e.g., 30 days) and then purged automatically.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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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: Table API — The Table API is the correct choice because it provides a fully managed, serverless NoSQL database with automatic TTL (Time-to-Live) for data expiration, low-latency point reads and writes by a composite key (partition key + row key), and is optimized for storing large volumes of structured log data with dynamic attributes. It supports the exact requirements: high-throughput writes, point queries by user ID and timestamp, and automatic expiration of old logs without manual intervention.
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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