easyMultiple Choice
FC0-U71 Practice Question: Store product catalogs that vary in structure…
A company wants to store product catalogs that vary in structure (different attributes per product). Which type of database is best suited?
⚠ Common exam trap
It's easy for candidates to default to relational databases for all structured data, failing to recognize that 'varying structure' is a key indicator for a NoSQL document store, not a relational or legacy database model.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Document database
A document database (NoSQL) is ideal for storing product catalogs with varying structures because it stores data in flexible, schema-less documents (e.g., JSON or BSON). Each product can have different attributes without requiring predefined columns or schema migrations, unlike relational databases. This allows the company to handle heterogeneous product data efficiently.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Relational database
Why it's wrong here
A relational database enforces a fixed schema of tables, rows and columns, so each product would need identical attributes or sparse nullable columns. It is tempting because relational engines handle transactions and joins well, and would be correct for catalogs with uniform, predefined attributes requiring referential integrity.
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Network database
Why it's wrong here
A network database enforces a fixed schema with records linked through predefined set structures, so it cannot accommodate per-product attribute variation without redesign. It is tempting because set-based pointers model many-to-many relationships efficiently, making it the right choice for hierarchical or networked data with stable, known structures.
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Hierarchical database
Why it's wrong here
Hierarchical databases enforce a fixed parent-child tree, so every product must share the same predefined attributes; varying structures cannot be represented without schema redesign. It is tempting because hierarchies suit rigid, one-to-many data such as file systems or bill-of-materials. A document or key-value store, which permits per-record attribute variation, satisfies this scenario.
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Document database
Why this is correct
A document database stores each product as a self-describing JSON-like document, so records can hold differing attribute sets without a fixed schema. That schema flexibility matches the stem's requirement for catalogs whose structure varies per product.
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