Quick Answer
The answer is indexes on nested fields. Amazon DocumentDB allows you to create indexes on specific paths within sub-documents, such as "address.city" or "items.sku", which enables the query engine to perform targeted index scans rather than full collection scans when you run ad-hoc queries on nested fields. This is the correct feature because without such indexes, DocumentDB would have to examine every document in the collection to match nested field conditions, which is inefficient for ad-hoc workloads. On the AWS Certified Database Specialty DBS-C01 exam, this concept tests your understanding of how DocumentDB’s MongoDB-compatible indexing works, and a common trap is assuming that enabling a search index or a text index is required—when in fact, a standard B-tree index on the nested path is sufficient. Remember the memory tip: “Nest the index, not the scan”—if you need to query deep, index the path.
This DBS-C01 practice question tests your understanding of deployment and migration. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 company is deploying a MongoDB-compatible database using Amazon DocumentDB. The application requires the ability to perform ad-hoc queries on nested fields within documents. Which DocumentDB feature should be enabled to meet this requirement?
TTL indexes
Why wrong: TTL indexes automatically delete documents after a period.
Indexes on nested fields
Indexes allow efficient ad-hoc queries on nested fields.
Transactions
Why wrong: Transactions provide ACID guarantees, not query optimization.
Change streams
Why wrong: Change streams capture changes, not query optimization.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Indexes on nested fields
Amazon DocumentDB supports indexing on nested fields, which allows efficient querying of sub-documents and arrays within documents. By creating indexes on specific nested paths (e.g., "address.city"), the query engine can perform index scans instead of full collection scans, enabling fast ad-hoc queries on nested fields. This feature directly meets the requirement for ad-hoc queries on nested fields.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
TTL indexes
Why it's wrong here
TTL indexes automatically delete documents after a period.
Indexes on nested fields
Why this is correct
Indexes allow efficient ad-hoc queries on nested fields.
Related concept
Read the scenario before looking for a memorised answer.
Transactions
Why it's wrong here
Transactions provide ACID guarantees, not query optimization.
Change streams
Why it's wrong here
Change streams capture changes, not query optimization.
Common exam traps
The trap here is that candidates may confuse indexing features with operational features like TTL or Change streams, assuming any advanced DocumentDB feature can support nested queries, when only explicit indexing on nested fields enables efficient ad-hoc querying on sub-documents.
Detailed technical explanation
When creating an index on a nested field in DocumentDB, the index key uses dot notation (e.g., db.collection.createIndex({"address.zip": 1})), which stores B-tree entries for the specific sub-field. This allows the query planner to use index intersection or index-only scans for queries like db.collection.find({"address.zip": "12345"}), significantly reducing I/O compared to scanning entire documents. A real-world scenario is an e-commerce application that needs to filter orders by nested shipping address fields without retrieving all documents.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
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FAQ
Deployment and Migration — This question tests Deployment and Migration — Read the scenario before looking for a memorised answer..
The correct answer is: Indexes on nested fields — Amazon DocumentDB supports indexing on nested fields, which allows efficient querying of sub-documents and arrays within documents. By creating indexes on specific nested paths (e.g., "address.city"), the query engine can perform index scans instead of full collection scans, enabling fast ad-hoc queries on nested fields. This feature directly meets the requirement for ad-hoc queries on nested fields.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
This DBS-C01 practice question is part of Courseiva's free Amazon Web Services 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 DBS-C01 exam.
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