Free MongoDB C100DEV Exam Questions

Become MongoDB Certified with updated C100DEV exam questions and correct answers

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Total 411 Questions | Updated On: Apr 20, 2026

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Question 1

You are developing a blogging platform using MongoDB as the database. Each blog post document has a tags array field that holds a list of strings. You are tasked to implement a search functionality that allows users to find blog posts based on the tags. Which of the following MongoDB features would you utilize to implement this functionality efficiently?

A : Capped Collections

B : Sharding

C : Text Indexes

D : Compound Indexes

E : GridFS

Answer: C

Question 2

In your database there is a collection named trips with the following document structure:

{

'_id': ObjectId("572bb8222b288919b68abf6d"),

'trip_duration': 858,

'start_station id': 532,

'end_station_id': 401,

'bike_id': 17057,

'start_station_loc': { type: 'Point', coordinates: [ -73.960876, 40.710451 ] },

'end_station_loc': { type: 'Point', coordinates: [ -73.98997825, 40.72019576 ] },

'start_time': ISODate("2016-01-01T00:09:31.000Z"),

'stop_time': ISODate("2016-01-01T00:23:49.000Z")

}

How can you extract all trips from this collection ended at stations that are to the west of the -73.5 longitude coordinate?

A : db.trips.find( { 'end_station_loc.coordinates.0': { $gt: -73.5 } } )

B : db.trips.find( { 'coordinates': { $lt: -73.5 } } )

C : db.trips.find( { 'end_station_loc.coordinates.0': { $lt: -73.5 } } )

D : db.trips.find( { 'end_station_loc.coordinates.1': { $lt: -73.5 } } )

Answer: C

Question 3

What is the best practice in using the $match operator?

A : It doesn't matter when we apply $match stage.

B : MongoDB does not have a $match stage.

C : The later in the pipeline, the better.

D : The earlier in the pipeline, the better. Not only because we will be using expression filters which reduce the number of documents to be processed, but also because we can use indexes.

Answer: D

Question 4

You have a MongoDB collection named students, where each document represents a student. The documents include fields like name, age, and courses. The courses field is an array that lists the course codes each student is enrolled in. You want to find all students enrolled in the course with the code "CS101". Which query will correctly retrieve all students enrolled in "CS101"?

A : db.students.find({ "courses": { $elemMatch: { $eq: "CS101" } } })

B : db.students.find({ "courses": [ "CS101" ] })

C : db.students.find({ "courses": { $in: "CS101" } })

D : db.students.find({ "courses": "CS101" })

Answer: D

Question 5

Consider a collection named orders with the following documents:

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e1"),

"order_number" : 1001,

"customer_id" : "CUST-001",

"order_date" : ISODate("2022-01-01T00:00:00Z"),

"total_amount" : 199.99

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e2"),

"order_number" : 1002,

"customer_id" : "CUST-002",

"order_date" : ISODate("2022-02-01T00:00:00Z"),

"total_amount" : 299.99

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e3"),

"order_number" : 1003,

"customer_id" : "CUST-003",

"order_date" : ISODate("2022-03-01T00:00:00Z"),

"total_amount" : 399.99

}

What is the query to create a compound index on the "customer_id" (ascending) and "order_date" (descending) fields in the orders collection?

A : db.orders.createIndex({ order_date: -1, customer_id: 1 })

B : db.orders.createIndex({ customer_id: asc, order_date: desc })

C : db.orders.createIndex({ customer_id: 1, order_date: -1 })

D : db.orders.createIndex({ customer_id: -1, order_date: 1 })

Answer: C

Page: 1 / 83

Total 411 Questions | Updated On: Apr 20, 2026

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