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: Jan 06, 2026
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Question 1

Suppose you're designing a MongoDB database for an online ticket booking system where millions of users can concurrently book tickets for various events. To maintain data consistency, you need to ensure that only one user can book a specific seat for an event at a time. Which MongoDB feature would you use to ensure data consistency in this high-concurrency situation?


Answer: A
Question 2

Consider a MongoDB database managing e-commerce product data. The database has a collection named products with documents containing the fields product_id, category, price, and reviews. Each reviews field is an array of subdocuments with fields user_id, rating, and comment. You are tasked with optimizing a query that retrieves all products within a specific category that have an average rating higher than 4. The query is frequently used, and performance is critical. Which indexing strategy would best optimize this query?


Answer: A
Question 3

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?


Answer: C
Question 4

We have a movies collection with the following document structure:
{
  _id: ObjectId("573a1390f29313caabcd6223"),
  genres: [ 'Comedy', 'Drama', 'Family' ],
  title: 'The Poor Little Rich Girl',
  released: ISODate("1917-03-05T00:00:00.000Z"),
  year: 1917,
  imdb: { rating: 6.9, votes: 884, id: 8443 }
},
{
  _id: ObjectId("573a13e3f29313caabdc08a4"),
  genres: [ 'Horror', 'Thriller' ],
  title: 'Mary Loss of Soul',
  year: 2014,
  imdb: { rating: '', votes: '', id: 2904798 }
}
We need to use Aggregation Framework to calculate the following aggregates:
average imdb rating
minimum imdb rating
maximum imdb rating
Expected output:
[
    {
        _id: null,
        avg_rating: 6.6934040649367255,
        min_rating: 1.6,
        max_rating: 9.6
    }
]
Please note that some documents have "" (empty string) for the field "imdb.rating". Exclude these documents before aggregation.
Which pipeline should you use?


Answer: C
Question 5

In your database there is a collection named companies with the following document structure:
{
  name: 'Wize',
  relationships: [
    {
      is_past: false,
      title: 'Head of Product',
      person: {
        first_name: 'Ethan',
        last_name: 'Smith',
        permalink: 'ethan-smith'
      }
    },
    {
      is_past: true,
      title: 'Director, Business Development',
      person: {
        first_name: 'Stephanie',
        last_name: 'Quay',
        permalink: 'stephanie-quay'
      }
    },
    {
      is_past: true,
      title: 'Sr. Engineer',
      person: {
        first_name: 'Stefan',
        last_name: 'Antonowicz',
        permalink: 'stefan-antonowicz'
      }
    }
  ]
}
Which of the following queries should you use to extract all companies that have "Co-Founder" title in relationships field (Array)?


Answer: B
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Total 411 Questions | Updated On: Jan 06, 2026
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