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: Feb 09, 2026
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Question 1

You are developing a MongoDB application where write performance is a critical requirement. Given a scenario where your application primarily performs insert operations and rarely performs updates or deletes, which of the following MongoDB features would best optimize this heavy-write workload?


Answer: D
Question 2

A MongoDB collection named logs is used to store event data for a web application. The collection originally had indexes on the timestamp, user_id, and event_type fields to facilitate fast queries on these fields. Due to a recent data archiving strategy, you decide to remove the index on event_type to save storage space. However, after doing so, some queries on the logs collection have slowed down considerably, especially those filtering by event_type. What is the most likely ramification of deleting the index on the event_type field?


Answer: D
Question 3

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 4

Suppose you have a reviews collection with the following index:
{ stars: 1, votes: 1 }
Which of the following queries would be a covered query?


Answer: D
Question 5

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
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Total 411 Questions | Updated On: Feb 09, 2026
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