Azure AI Search Integration
← Back to DP-420 Terminology Reference
Category: Integration & Analytics
Summary: Indexer pulls Cosmos DB data (via change feed) to enable full-text/semantic search.
Overview
Azure Cosmos DB integrates with Azure AI Search to enable full-text and semantic search over Cosmos DB data by configuring an Azure AI Search indexer that pulls data from a Cosmos DB container (often via the change feed for incremental indexing), so applications can perform rich search queries beyond what Cosmos DB's native query capabilities provide.
More Info & Links
DP-420 Style Practice Questions
Q1. Why would you integrate Azure Cosmos DB with Azure AI Search?
- A. To enable rich full-text/semantic search capabilities over Cosmos DB data beyond native query features
- B. To enable multi-region writes
- C. To reduce RU consumption on point operations
- D. To enforce unique key constraints
Q2. How does an Azure AI Search indexer typically stay up to date with changes in a Cosmos DB container?
- A. By leveraging the change feed for incremental indexing
- B. By performing a full container scan on every search query
- C. By requiring manual re-indexing after every write
- D. By using a stored procedure triggered per search request
Answer Key
Answers are listed at the very end so you can attempt the questions first.
- Q1 (Azure AI Search Integration): A. To enable rich full-text/semantic search capabilities over Cosmos DB data beyond native query features — Azure AI Search adds full-text and semantic search capabilities over data stored in Azure Cosmos DB.
- Q2 (Azure AI Search Integration): A. By leveraging the change feed for incremental indexing — Azure AI Search indexers can use the change feed to efficiently and incrementally pick up new/updated items.
DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB — term detail page
