C100DEV Data Modeling Practice Question
You have a document with an unbounded array of data. Which TWO strategies help mitigate the risk of exceeding the 16MB document size limit?
⚠ Common exam trap
Candidates tend to choose sharding as a solution for unbounded arrays within a single document, missing that sharding operates at the collection level, not the document level.
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
✓
Implement the subset pattern to store only the most recent items in the document.
Managing document growth is critical for long-term stability. The 'subset pattern' keeps only the most relevant items embedded, while 'bucketing' groups related items into separate documents to prevent a single document from growing indefinitely. Both techniques ensure that documents remain performant and well below the 16MB threshold, preventing application crashes when arrays grow beyond predicted sizes over time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Implement the subset pattern to store only the most recent items in the document.
Why this is correct
The subset pattern limits document size by storing only the most frequently accessed data inside the main document. Older or less relevant data is offloaded to a separate collection. This keeps the primary document compact, ensures faster scans, and prevents the 16MB document size limit from being reached.
- ✗
Increase the maximum BSON document size limit in the mongod configuration file.
Why it's wrong here
The 16MB document size limit is a hard-coded constraint in MongoDB to ensure efficient memory usage and performance. It cannot be modified via configuration. Attempting to bypass this limit is not possible and indicates an architectural flaw in the data model that requires refactoring to handle data volume.
- ✓
Use the bucketing pattern to group array items into multiple documents.
Why this is correct
Bucketing involves splitting a large dataset into multiple smaller documents based on criteria like time intervals or specific counts. This prevents any single document from growing unbounded, keeps individual document sizes small, and allows for efficient querying across the range of documents representing the full dataset.
- ✗
Convert the array to a single large string field to save space.
Why it's wrong here
Converting an array to a single string makes data harder to query, index, and manipulate within MongoDB. It does not solve the underlying growth issue, as the string itself will eventually exceed the 16MB limit, while also losing the ability to use powerful array-specific operators for filtering.
- ✗
Disable indexing on all array fields to prevent size expansion.
Why it's wrong here
Disabling indexes does not reduce the actual size of the BSON document stored on disk. It only affects query performance and index memory usage. Furthermore, indexing is essential for query efficiency; removing it will hurt performance without addressing the core problem of reaching the document size limit.
About these practice questions
This C100DEV question is part of Courseiva's 259-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official MongoDB exam blueprint
This C100DEV practice question is part of Courseiva's free MongoDB 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 C100DEV exam.