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

Embedding stores related data in a single document as nested subdocuments, improving read performance by avoiding joins but potentially increasing document size.

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

References (storing related document _ids) are preferred when related data is large, changes frequently, or is shared by multiple parent documents.

Question 3

What is MongoDB's document size limit?

Accepted Answer

16 MB

Answer

MongoDB limits individual documents to 16 MB, which prevents excessive memory usage and encourages proper data modeling.

Question 4

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

Accepted Answer

Grouping time-series data into documents covering a time range

Answer

The bucket pattern groups related time-series data into documents that each cover a defined time period, reducing the number of documents and improving query performance.

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

The outlier pattern handles edge cases where most documents have small arrays but a few have very large ones by storing overflow data in additional linked documents.

MongoDB Practice Test

MongoDB Practice Test

MongoDB MongoDB Data Modeling