mediummultiple choiceObjective-mapped

A logistics company stores shipment tracking data as JSON documents in Azure Cosmos DB. Each document contains fields like trackingId, origin, destination, status, weight, and optional fields (estimatedDelivery, carrierNotes). The application needs to perform low-latency lookups by trackingId and also run queries to find all shipments that have a specific origin and status. Which Azure Cosmos DB API should they choose?

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A logistics company stores shipment tracking data as JSON documents in Azure Cosmos DB. Each document contains fields like trackingId, origin, destination, status, weight, and optional fields (estimatedDelivery, carrierNotes). The application needs to perform low-latency lookups by trackingId and also run queries to find all shipments that have a specific origin and status. 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

Distractor review

Table API

The Table API is optimized for simple key-value lookups and does not provide rich query capabilities for filtering on multiple properties.

B

Best answer

SQL (Core) API

The SQL API supports querying JSON documents with standard SQL syntax, indexes all properties automatically, and allows both point reads and filter queries efficiently.

C

Distractor review

MongoDB API

While the MongoDB API can handle similar scenarios, it may not offer the same ease for multi-field queries and typically requires explicit index creation for best performance.

D

Distractor review

Gremlin API

The Gremlin API is designed for graph-based data with vertices and edges, not for general JSON documents or queries on properties like origin and status.

Common exam trap

Common exam trap: NAT rules depend on direction and matching traffic

NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.

Technical deep dive

How to think about this question

NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.

KKey Concepts to Remember

  • Static NAT maps one inside address to one outside address.
  • PAT allows many inside hosts to share one public address using ports.
  • Inside local and inside global describe the private and translated addresses.
  • NAT ACLs identify traffic for translation, not always security filtering.

TExam Day Tips

  • Identify inside and outside interfaces first.
  • Check whether the scenario needs static NAT, dynamic NAT or PAT.
  • Do not confuse NAT matching ACLs with normal packet-filtering intent.

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?

Static NAT maps one inside address to one outside address.

What is the correct answer to this question?

The correct answer is: SQL (Core) API — The SQL (Core) API is the native API for Azure Cosmos DB and provides full SQL query capabilities over JSON documents. It supports automatic indexing on all properties, making it easy to query by trackingId (key lookup) and filter by multiple fields like origin and status. The Table API is designed for key-value workloads and does not natively support complex queries. The MongoDB API is compatible with MongoDB drivers but lacks some SQL features and may require additional configuration for efficient queries on multiple fields. The Gremlin API is for graph data and is not suited for this document query pattern.

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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