AI-200 Data Management Services And Vector Search Practice Question
You are designing an application that stores vector embeddings in Azure SQL Database. Which data type should you use to store vector data natively in modern Azure SQL?
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
✓
VECTOR native data type
Azure SQL Database supports the vector data type (along with native vector functions like vector_distance) to store and query high-dimensional embeddings 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.
- ✗
VARCHAR(MAX) JSON string
Why it's wrong here
Storing vectors as serialized JSON strings prevents efficient distance calculations in the database engine.
- ✓
VECTOR native data type
Why this is correct
The VECTOR data type is the native storage format in Azure SQL Database for vector embeddings.
- ✗
FLOAT array collection
Why it's wrong here
FLOAT arrays are not a native column type in Azure SQL Database.
- ✗
VARBINARY(MAX) blob
Why it's wrong here
While binary blobs can store raw bytes, Azure SQL provides a dedicated native vector data type for optimal performance.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-200 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-200 exam.