MongoDB MongoDB Data Modeling

Question 1

What is the embedded document (denormalized) data model in MongoDB?

Accepted Answer

Storing related data as nested subdocuments within a single document

Answer

Storing related data as separate referenced documents

Answer

Embedding JavaScript functions in documents

Answer

Using base64 encoding for binary data

Question 2

When should you prefer the reference (normalized) data model over embedding?

Accepted Answer

When data is frequently accessed independently or shared across multiple documents

Answer

When documents are always queried together

Answer

When data is rarely accessed

Answer

When documents are small and simple

Question 3

What is MongoDB's document size limit?

Accepted Answer

16 MB

Answer

1 MB

Answer

4 MB

Answer

64 MB

Question 4

What is the 'bucket pattern' in MongoDB data modeling?

Accepted Answer

Grouping time-series data into documents covering a time range

Answer

Distributing documents across multiple collections

Answer

Storing binary data in chunks

Answer

Creating separate collections per user

Question 5

What is the 'outlier pattern' in MongoDB data modeling used for?

Accepted Answer

Handling documents whose arrays would exceed the size limit by using overflow documents

Answer

Handling documents with unusually large field counts

Answer

Filtering statistical outliers in queries

Answer

Handling rare edge cases in schema validation

Question 6

Which of the following best describes a polymorphic schema in MongoDB?

Accepted Answer

A collection storing documents with varying but related structures

Answer

A schema that changes automatically over time

Answer

A schema generated from multiple programming languages

Answer

A schema that inherits from a parent schema