Why document databases over relational in MongoDB - Challenge Your Understanding

Challenge - 5 Problems

🧠 Conceptual

intermediate

Advantages of Document Databases for Flexible Data

Which of the following is a key reason to choose a document database over a relational database?

A Document databases require fixed schemas for all documents.

B Relational databases automatically scale horizontally without extra setup.

C Document databases allow storing data with varying structures easily in one collection.

D Relational databases store data as JSON documents natively.

💡 Hint

Think about how data structure flexibility affects storing different types of records.

Document databases store data as flexible JSON-like documents, allowing different fields per record without schema changes. Relational databases require fixed tables and columns.

❓ query_result

intermediate

Query Result: Embedded Documents in MongoDB

Given a MongoDB collection users where each document has an embedded address object, what will this query return?

db.users.find({"address.city": "Seattle"})

A All user documents where the city in the address is Seattle.

B All users regardless of city because the query is invalid.

C An error because embedded fields cannot be queried.

D Only the address subdocuments with city Seattle, not the whole user documents.

💡 Hint

Think about how MongoDB queries nested fields inside documents.

The query matches documents where the embedded field address.city equals "Seattle" and returns the whole matching documents.

📝 Syntax

advanced

Correct MongoDB Insert Syntax for Nested Document

Which option correctly inserts a document with a nested profile object into a MongoDB collection members?

MongoDB

db.members.insertOne({name: "Alice", profile: {age: 30, city: "Boston"}})

A db.members.insertOne({name: "Alice", profile: {age: 30, city: "Boston"}})

B db.members.insertOne({name: "Alice", profile: "age: 30, city: Boston"})

C db.members.insertOne({name: "Alice", profile: (age: 30, city: "Boston")})

D db.members.insertOne({name: "Alice", profile: [age: 30, city: "Boston"]})

💡 Hint

Remember the syntax for nested objects in JSON-like documents.

Option A uses correct JSON object syntax for the nested profile. Options A and C use invalid brackets, and D uses a string instead of an object.

❓ optimization

advanced

Optimizing Queries with Indexes in Document Databases

You have a MongoDB collection with millions of documents. You often query by the field email. Which option best improves query speed?

A Use a text search index on all fields.

B Create an index on the <code>email</code> field.

C Store emails in a separate collection and join on query.

D Add a unique constraint on the <code>email</code> field but no index.

💡 Hint

Think about how databases speed up lookups on specific fields.

Creating an index on the email field allows fast lookups. Unique constraints also create indexes, but just adding a constraint without an index is not possible. Text search indexes are for full-text search, not exact matches.

🔧 Debug

expert

Why Does This MongoDB Update Not Change the Document?

Given this update command, why does the document remain unchanged?

db.products.updateOne({name: "Pen"}, {price: 1.5})

A The collection name <code>products</code> is reserved and cannot be updated.

B The query filter is incorrect and matches no documents.

C MongoDB does not allow updating numeric fields directly.

D The update document is missing an update operator like <code>$set</code>.

💡 Hint

Think about how MongoDB expects update commands to be structured.

MongoDB update commands require update operators like $set to specify which fields to change. Without it, MongoDB treats the second argument as a replacement document, which must contain the full document. Here, it tries to replace the document with only {price: 1.5}, which fails silently if the filter matches.