C100DBA Philosophy and Features Practice Question
A healthcare analytics team stores patient records in MongoDB. Each record includes a nested array of vital sign readings, and the team frequently queries for patients whose latest blood pressure reading exceeds a threshold. They decide to store each reading as a separate document in a readings collection and reference the patient. Which MongoDB design philosophy does this decision contradict?
⚠ Common exam trap
The trap here is assuming that any referencing is always wrong, when in fact referencing is appropriate for large, unbounded arrays or data accessed independently.
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
✓
Data that is accessed together should be stored together.
The team's choice to reference readings instead of embedding them conflicts with the core MongoDB principle that related data accessed together should be stored together. Embedding the readings array within the patient document would allow a single query to retrieve the latest blood pressure without additional lookups, improving performance and simplifying application logic. This principle guides schema design for locality and efficiency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use server-side JavaScript for all data validation.
Why it's wrong here
Server-side JavaScript is not a core design philosophy of MongoDB, and modern MongoDB versions deprecate server-side JavaScript execution for security and performance reasons. The team's decision to reference rather than embed has nothing to do with validation logic. This option is a distractor because it introduces an unrelated technical mechanism that does not address the query access pattern.
- ✗
Store all data in a single collection to simplify sharding.
Why it's wrong here
MongoDB does not advocate storing all data in a single collection; such a design would harm query performance and index efficiency. Sharding can be applied to multiple collections, and the philosophy focuses on modeling based on access patterns, not on consolidating everything. This option misrepresents MongoDB's guidance and does not relate to the embedding versus referencing decision described.
- ✓
Data that is accessed together should be stored together.
Why this is correct
MongoDB's document model encourages embedding related data that is queried together. By separating readings into another collection, the team forces an extra query or $lookup to retrieve the latest reading, increasing latency and complexity. Embedding the readings array within the patient document aligns with the principle of locality of access, which is central to MongoDB's design philosophy.
- ✗
Normalize all data to the third normal form to eliminate redundancy.
Why it's wrong here
Third normal form is a relational database concept that MongoDB does not enforce or recommend as a design goal. While avoiding unnecessary duplication is good practice, strict normalization often leads to excessive referencing and joins, which contradicts MongoDB's document-oriented approach. The scenario's issue is not about normalization but about separating data that is typically accessed together.
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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 C100DBA 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 C100DBA exam.