MongoDB Associate Developer Exam Questions 2025

A developer using MongoDB with their application must possess the knowledge and skills necessary to utilize the database effectively. This means that they must have hands-on experience completing day-to-day operational tasks needed to use MongoDB. At a minimum, it’s recommended that the candidate has:

• Software engineering experience (any programming language)
• Successfully completed MongoDB training (or equivalent hands-on experience using MongoDB as the backing database for an application)

Below knowledge is recommended for MongoDB Associate Developer Exam 2025:

The exam objectives and topic-level weighting are below for your reference. Use them to guide your study and to prepare for the exam.

Section 1: MONGODB OVERVIEW AND THE DOCUMENT MODEL (8%)

• Identify the set of value types MongoDB BSON supports.
• Given three documents that are of different shapes, identify which can co-exist in the same collection.

Section 2: CRUD (51%)

• Given a scenario with a type of structured document that needs to be inserted into a database, identify properly and improperly formed insert commands.
• Given an update scenario where an entire updated document (no update operators used) is provided, identify the output and how the database changed state.
• Given an update scenario where $set is used, identify the output and how the database changed state.
• Given a scenario about updating a document and information about where it should be inserted if it does not exist, identify the upsert command that should be used.
• Given a scenario where multiple documents need to be updated, identify the correct update expression.
• Given a findAndModify scenario where another operation is run concurrently, identify the output and how the database changed state.
• Given a scenario where a document should be deleted from the database, identify the delete expression that should be used.
• Given a scenario where a single document should be looked up by a simple equality constraint (e.g., {x: 3}), identify the expression that should be used.
• Identify documents matched by a query with an equality constraint on an array field.
• Identify documents matched by an expression with relational operators in it.
• Identify documents matched by an expression with $in.
• Identify documents matched by a $elemMatch expression.
• Identify documents matched by an expression that has several logical operators.
• Given a query with a sort and limit, identify the correct output.
• Identify the incorrect projection among a set of expressions.
• Identify how to get all results from a cursor.
• Identify the expressions used to count the number of documents matching a query.
• Given an indexing scenario, identify the correct command for defining a search index.
• Given a scenario, identify the correct search query.
• Given an aggregation expression using $match, $group, identify the correct output.
• Given an aggregation expression using $lookup, identify the correct output.
• Given an aggregation expression using $out, identify the correct output.

Section 3: INDEXES (17%)

• Given a query that is performing a collection scan, identify which index would improve the performance of this query.
• Given a query that is performing a collection scan on an equality match on an array field, identify which index would improve the performance of this query.
• Given a query with no constraint and a sort of two fields that is doing a collection scan, identify which index would improve the performance of this query.
• Given a collection, identify how many indexes exist for that collection.
• Identify poor production practices.
• Identify the explain plan outputs that signify a potential performance issue, specifically whether an index is present or not for the given query.

Section 4: DATA MODELING (4%)

• Given a scenario with three collections (a parent and two children) and the user, identify the embedded relationships and which should be linked.
• Identify data model examples that are considered an anti-pattern.

Section 5: TOOLS AND TOOLING (2%)

• Given a scenario to load the Atlas Sample Dataset and then use Data Explorer to find a given first document in a collection.

Section 6: DRIVERS (18%)

• Define what the XX driver is.
• Define how the XX application connects/uses the XX driver.
• Define the components of the URI string used by MongoClient to connect the driver to the database.
• Identify what connection pooling is in terms of the driver and what advantages it offers.
• Identify the correct syntax for the XX driver to insert one document and to insert many documents.
• Identify the correct syntax for the XX driver to update one document and to update many documents.
• Identify the correct syntax for the XX driver to delete one document and to delete many documents.
• Identify the correct syntax for the XX driver to find many documents and to find one document.
• Identify the correct syntax for the XX driver to create an aggregation pipeline.
• Identify the different syntax for the XX driver when using the MongoDB Query Language (MQL) and when using the Aggregation Framework.

(Note: The MongoDB Associate Developer exam is offered in multiple programming languages. Although they all share a common set of core questions, Section 6 – Drivers, will be presented according to the programming language selected during registration.)

Exam Details

• Format: 53 Multiple choice questions
• Time allotted: 75 Minutes
• Exam fee: USD $150
• Delivery Options: Online in a proctored environment
• Prerequisites: None
• Language: English