AI-200 Data Management Services And Vector Search Practice Question
You are configuring an Azure AI Search vector index for a retrieval-augmented generation (RAG) application. You need to select an algorithm for vector similarity search that balances recall speed with accuracy while allowing approximate nearest neighbor (ANN) search. Which vector search algorithm configuration should you select?
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
✓
Hierarchical Navigable Small World (hnsw)
HNSW (Hierarchical Navigable Small World) is the industry-standard algorithm used by Azure AI Search for approximate nearest neighbor (ANN) vector search, providing an optimal balance between fast retrieval speed and high recall.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Exhaustive K-Nearest Neighbor (exhaustiveKnn)
Why it's wrong here
Exhaustive k-nn performs exact nearest neighbor search by comparing the query vector against every stored vector, which guarantees 100% recall but scales poorly in latency for large datasets.
- ✓
Hierarchical Navigable Small World (hnsw)
Why this is correct
HNSW is the approximate nearest neighbor algorithm supported in Azure AI Search that provides high search performance and accuracy.
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Locality-Sensitive Hashing (lsh)
Why it's wrong here
Locality-Sensitive Hashing is not natively supported as a primary index algorithm configuration in Azure AI Search.
- ✗
Inverted File with Product Quantization (ivf-pq)
Why it's wrong here
While IVF-PQ is common in other vector databases, Azure AI Search relies on HNSW and exhaustive KNN for its vector search implementation.
About these practice questions
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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.