Tables vs collections thinking in MongoDB - Practice Questions

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding the difference between tables and collections

In MongoDB, which statement best describes the difference between a table in SQL and a collection in MongoDB?

A A table and a collection are exactly the same, both store data in fixed schemas with rows and columns.

B A table stores data as JSON documents, while a collection stores data in rows and columns.

C A table stores data in rows and columns with a fixed schema, while a collection stores documents that can have varying fields and structures.

D A table is used only for temporary data, while a collection stores permanent data.

💡 Hint

Think about how flexible the data structure is in MongoDB compared to SQL.

Tables in SQL databases have fixed schemas with rows and columns. Collections in MongoDB store documents that can have different fields and structures, allowing more flexibility.

❓ query_result

intermediate

Query result difference between SQL and MongoDB

Given a SQL table users with columns id and name, and a MongoDB collection users with documents having fields _id and name, what would be the result of the following MongoDB query?

db.users.find({ name: "Alice" })

Assuming the collection has these documents:

[{ _id: 1, name: "Alice" }, { _id: 2, name: "Bob" }, { _id: 3, name: "Alice", age: 30 }]

A []

B [{ _id: 1, name: "Alice" }, { _id: 3, name: "Alice", age: 30 }]

C [{ _id: 2, name: "Bob" }]

D [{ id: 1, name: "Alice" }]

💡 Hint

The query filters documents where the name field equals "Alice".

The query returns all documents where the name field is "Alice". Both documents with _id 1 and 3 match, including the one with an extra age field.

📝 Syntax

advanced

Identify the invalid MongoDB collection creation syntax

Which of the following commands will cause a syntax error when creating a collection in MongoDB?

A db.createCollection("orders", { capped: true, size: 5242880 })

B db.createCollection("products")

C db.products.insertOne({ name: "Book", price: 12.99 })

D db.createCollection(products)

💡 Hint

Look for missing quotes or incorrect argument types.

Option D is invalid because the collection name must be a string enclosed in quotes. Without quotes, it causes a syntax error.

❓ optimization

advanced

Optimizing data retrieval in collections vs tables

You have a large SQL table and a MongoDB collection both storing user data. Which approach is generally faster for retrieving a user by their unique ID?

A MongoDB's default _id index provides fast retrieval similar to SQL primary key indexes, so both are generally equally fast.

B MongoDB collections do not support indexes, so SQL tables are always faster.

C Using an indexed primary key in SQL tables is generally faster than MongoDB's default _id index.

D MongoDB requires scanning the entire collection, so SQL tables are faster for unique ID lookups.

💡 Hint

Think about how both systems index unique identifiers.

Both SQL tables and MongoDB collections use indexes on unique IDs (_id in MongoDB, primary key in SQL) to quickly retrieve data, making their performance similar for such queries.

🔧 Debug

expert

Debugging schema design misunderstanding between tables and collections

A developer tries to enforce a fixed schema in a MongoDB collection by creating a table-like structure with all fields mandatory. Which problem will most likely occur?

A MongoDB allows flexible schemas, so documents missing some fields will be accepted, leading to inconsistent data.

B MongoDB will reject any document that does not have all fields, causing frequent insertion errors.

C MongoDB automatically fills missing fields with null values to enforce the schema.

D MongoDB converts the collection into a SQL table to enforce the schema.

💡 Hint

Consider MongoDB's schema flexibility and validation behavior by default.

MongoDB collections are schema-less by default, so documents missing some fields are accepted unless explicit validation rules are set. This can lead to inconsistent data if a fixed schema is expected but not enforced.