AI-200 Data Management Services And Vector Search Practice Question
Your enterprise application architecture incorporates Azure Cosmos DB for NoSQL as the primary operational data store and Azure AI Search as the vector index for semantic search. Which THREE mechanisms can you use to keep the Azure AI Search vector index synchronized with changes in Azure Cosmos DB?
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
✓
Configure an Azure AI Search indexer connected to an Azure Cosmos DB change feed data source.
Syncing Azure Cosmos DB with Azure AI Search can be achieved natively using Azure Cosmos DB change feed integration via Azure Functions, using built-in Azure AI Search indexers configured with an Azure Cosmos DB change feed data source, or via custom event-driven pipelines using Azure Event Grid.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure an Azure AI Search indexer connected to an Azure Cosmos DB change feed data source.
Why this is correct
Azure AI Search provides a native indexer for Azure Cosmos DB for NoSQL that tracks changes automatically using the change feed.
- ✓
Use Azure Event Grid to capture container mutation events and orchestrate indexing updates.
Why this is correct
Azure Event Grid integrates with Azure Cosmos DB to trigger workflows upon data modification, enabling custom synchronization logic.
- ✓
Deploy an Azure Function triggered by the Azure Cosmos DB change feed to push document inserts and updates directly to the Azure AI Search REST API.
Why this is correct
An Azure Function bound to the Cosmos DB change feed is a standard, highly flexible pattern for real-time synchronization to search indexes.
- ✗
Execute a full database table scan and drop-rebuild of the search index every 5 minutes using Azure Data Factory batch pipelines.
Why it's wrong here
Dropping and rebuilding indexes periodically is inefficient, causes downtime, and fails to provide near real-time synchronization.
- ✗
Enable native real-time bidirectional memory-mapped replication between Azure Cosmos DB database partitions and search service replicas.
Why it's wrong here
No such native bidirectional memory-mapped replication feature exists between Cosmos DB partitions and AI Search replicas.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
About these practice questions
One of 507 original AI-200 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
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.