MongoDB Developer Sample Questions & Practice Test

MongoDB Associate Developer is a developer route for candidates who use MongoDB from application code, write queries and updates, design document access patterns, use indexes, and reason through aggregation or transaction behavior.

Use this page to preview the kind of developer decisions a MongoDB practice route should test. The questions below are original IT Mastery sample questions, not official MongoDB exam questions.

What this route should test

• choosing document shapes and query patterns that fit application access needs
• writing CRUD, update, aggregation, and transaction decisions from requirements
• understanding index behavior, query selectivity, and driver-level application concerns
• separating database modeling issues from application logic, network, and deployment issues

Sample Exam Questions

Question 1

Topic: document shape

An application always displays an order with its line items, and line items are rarely queried independently. Which model is usually best?

• A. Store each line item in a separate collection and join at read time for every order view
• B. Embed line items inside the order document, assuming document size remains reasonable
• C. Store all line items in one global document
• D. Duplicate the entire customer database inside each order

Best answer: B

Explanation: Embedding fits data that is read together and has a bounded size. It avoids extra lookups for the common order view while keeping the document aligned with the application’s access pattern.

Question 2

Topic: indexes

A query filters on { status: "open", customerId: ... } and sorts by createdAt. What should the developer consider?

• A. Only adding a text index on every field
• B. Removing all filters
• C. A compound index that matches the filter and sort pattern where appropriate
• D. Turning the collection into one document

Best answer: C

Explanation: Compound indexes can support filters and sort operations when ordered to match the query pattern. The exact index order depends on selectivity and the workload, but a generic text index is not the answer.

Question 3

Topic: update operators

Which update is safest when incrementing a numeric loginCount field?

• A. Use an update operator such as $inc
• B. Read the document, add one in application memory, then replace the whole document without checking concurrency
• C. Delete and reinsert the user document
• D. Store the count in the collection name

Best answer: A

Explanation: $inc performs an atomic increment on the field. Replacing the whole document can lose concurrent updates if not carefully controlled.

Question 4

Topic: aggregation

A report needs total revenue by month for completed orders. Which feature is most relevant?

• A. A shell prompt color
• B. A random collection rename
• C. A backup restore only
• D. An aggregation pipeline with filtering, grouping, and summing stages

Best answer: D

Explanation: Aggregation pipelines transform and summarize documents. Filtering completed orders, grouping by month, and summing revenue directly matches the report requirement.

Question 5

Topic: projections

Why should a query use projection when the application needs only three fields from large documents?

• A. To delete unused fields permanently
• B. To limit returned data and reduce transfer and processing overhead
• C. To make writes impossible
• D. To ignore all indexes

Best answer: B

Explanation: Projection controls which fields are returned. It can reduce network transfer and application processing, especially when documents contain large fields not needed by the view.

Question 6

Topic: transactions

When might a multi-document transaction be justified?

• A. For every read-only query
• B. To replace all indexes
• C. When related writes across multiple documents must commit or roll back together
• D. To avoid all schema design decisions

Best answer: C

Explanation: Transactions support atomicity across multiple documents or collections when required. They are not a substitute for good modeling and should not be used unnecessarily for simple single-document operations.

Question 7

Topic: drivers

What should application code do with database connection handling?

• A. Use the driver connection-management pattern recommended for the application framework
• B. Create a new client for every document read and never reuse it
• C. Store database credentials in public source code
• D. Disable timeouts

Best answer: A

Explanation: Drivers are designed with connection management patterns such as pooling. Applications should follow driver and framework guidance instead of repeatedly opening connections or embedding secrets.

Question 8

Topic: query troubleshooting

A query is unexpectedly slow. What should be reviewed first?

• A. Only the collection name
• B. The user’s browser zoom
• C. Whether the code comments are long
• D. Query shape, indexes, selectivity, sort requirements, returned fields, and execution plan evidence

Best answer: D

Explanation: Query performance depends on filters, indexes, cardinality, sorting, projection, and execution path. Developers should use evidence before changing the model or adding broad indexes.

Question 9

Topic: schema validation

Why might a team use schema validation in MongoDB?

• A. To convert MongoDB into a spreadsheet
• B. To enforce selected document structure rules while still using a document model
• C. To prevent all application bugs
• D. To remove all indexes

Best answer: B

Explanation: Schema validation can enforce required fields, types, or constraints where consistency matters. It does not eliminate the need for application validation and testing.

Question 10

Topic: read preference

What is a key risk of reading from secondaries in a replica set?

• A. Queries become encrypted automatically
• B. Writes become impossible everywhere
• C. Reads may be stale depending on replication lag and read concern choices
• D. Indexes are no longer used

Best answer: C

Explanation: Secondary reads can improve read scaling or locality, but they may not reflect the latest primary writes. Developers must understand consistency requirements.

Question 11

Topic: error handling

A write fails with a duplicate key error. What does that usually indicate?

• A. A unique index constraint was violated
• B. The server has no collections
• C. The aggregation pipeline is always wrong
• D. The driver cannot read JSON

Best answer: A

Explanation: Duplicate key errors commonly occur when an insert or update violates a unique index. The application should handle the conflict according to business rules.

Question 12

Topic: data modeling

A product document has a growing unbounded array of user activity events. What is the likely modeling concern?

• A. Arrays are never allowed in MongoDB
• B. The product name must be numeric
• C. Indexes cannot exist on any collection with arrays
• D. Unbounded arrays can make documents grow too large and inefficient to update or read

Best answer: D

Explanation: Embedding is useful for bounded, related data. Unbounded event history can create large documents and update hot spots, so a separate collection or bucketing pattern may be better.

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