Hire Pre-vetted MongoDB talents

Here are five questions that can be asked during a technical interview with MongoDB developers:

Question 1: How are queries performed in MongoDB?

This question tests if the developer understands different ways to apply filtering to MongoDB queries.
A strong answer would explain:

"Querying can be done in MongoDB using the find method, and the selection criteria are based on the query parameter passed to find."

Code snippets can also be used to demonstrate examples.

View example MongoDB query snippet

A good response should also describe the process of filtering and what results are returned.

Question 2: What are indexes in MongoDB?

This question evaluates if the developer understands:

• The impact of indexes

• How they are implemented

• How they improve query performance

A good answer:

"Indexes are structures that help MongoDB quickly find the documents matching a query without scanning the entire collection."

Without indexes, MongoDB must scan all documents, which slows down performance.
Single field and compound indexes are among the most common.

View example MongoDB indexing snippet

Candidates should also mention memory allocation considerations and best practices like planning indexes based on query patterns.

Question 3: What is the difference between MapReduce and the Aggregation Pipeline in MongoDB?

This question assesses understanding of large data set processing and optimization.

A strong answer:

• Both MapReduce and Aggregation Pipeline use stages to filter and transform data.

• MapReduce uses single-threaded JavaScript (SpiderMonkey engine) — slower.

• Aggregation Pipeline uses compiled C++ — much faster and preferred.

Bonus: MapReduce is no longer supported starting from MongoDB version 5.0.

View MapReduce code snippet
View aggregation alternative (customer ID totals)
Aggregation pipeline version

Question 4: What are the important points to consider when creating a schema in MongoDB?

This assesses schema design best practices.

Key points to mention:

• Understand user requirements, data types, query patterns, and available hardware

• Embed documents if used together frequently; separate otherwise

• Avoid documents exceeding 16MB default size

• Use field modifiers for updates to improve performance

• Use schema denormalization and embedded documents wisely

• Plan and create indexes to optimize queries

• Override the default _id field if needed for better sorting or access

A strong candidate should explain that a well-designed schema is critical to database scalability, speed, and cost-efficiency.

Question 5: What is sharding in MongoDB?

This question tests understanding of MongoDB’s scaling strategy.

A great answer:

"Sharding is the process of distributing data across multiple MongoDB instances to handle larger data volumes and maintain performance."

Important notes:

• Shards are separate MongoDB instances each holding a subset of the data.

• Sharded clusters require careful setup, planning, and maintenance.

• Once a collection is sharded, it cannot be unsharded.

• Sharding uses horizontal scaling to improve throughput.