MongoDB Data Modeling Flashcards

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

Answer: Storing related data as nested subdocuments within a single document

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

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

Answer: When data is frequently accessed independently or shared across multiple documents

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

What is MongoDB's document size limit?

Answer: 16 MB

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

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

Answer: Grouping time-series data into documents covering a time range

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.

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

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

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.

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

Answer: A collection storing documents with varying but related structures

Polymorphic schema allows different documents in the same collection to have different fields while still representing related entities.