AI-102 Implement generative AI solutions Practice Question
Which TWO Azure services can be used together with Azure OpenAI to implement a Retrieval-Augmented Generation (RAG) solution?
⚠ Common exam trap
A common mix-up: candidates assume any storage service (like Blob Storage or SQL Database) can directly support RAG, but they overlook the need for native vector search or hybrid retrieval capabilities that only Azure AI Search and Cosmos DB (with vector support) provide.
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
✓
Azure Cosmos DB
Azure Cosmos DB is correct because it can serve as a vector database for storing and querying embeddings generated by Azure OpenAI. When combined with Azure AI Search, which provides hybrid search (vector + keyword) and indexing capabilities, it enables a complete RAG pipeline where relevant documents are retrieved and passed as context to the OpenAI model for grounded generation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Blob Storage
Why it's wrong here
Blob Storage is for file storage, not search.
- ✓
Azure Cosmos DB
Why this is correct
Cosmos DB supports vector indexing.
- ✓
Azure AI Search
Why this is correct
Azure AI Search provides vector and hybrid search.
- ✗
Azure SQL Database
Why it's wrong here
SQL Database lacks native vector search.
- ✗
Azure Functions
Why it's wrong here
Functions is compute, not a data store.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 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-102 exam.