Microsoft Azure → Amazon Web Services
AWS equivalent of Azure AI Search
The closest AWS equivalents of Azure AI Search are Amazon S3 Vectors, Amazon Bedrock Knowledge Bases and Amazon Kendra.
About Azure AI Search
| Provider | Microsoft Azure |
|---|---|
| Status | Generally available The product docs still say "Azure AI Search", but the Azure pricing page for it is now titled "Foundry IQ". |
| What it is | Search and retrieval engine. Full-text, vector, and hybrid search, semantic ranker, integrated vectorization and AI enrichment (indexers and skillsets), and agentic retrieval. |
| Documentation | learn.microsoft.com |
| Pricing | Official pricing page |
AWS mappings (3)
| Capability | AWS equivalent | Match |
|---|---|---|
| Low-cost vector storage and similarity search | Amazon S3 Vectors | Partial match |
| Managed RAG / knowledge bases | Amazon Bedrock Knowledge Bases | Direct match |
| Enterprise / intelligent search | Amazon Kendra Maintenance, Amazon Bedrock Knowledge Bases | Partial match |
Object access, file access & analytics(1)
Low-cost vector storage and similarity search Partial match
Amazon S3 Vectors has no Azure storage-layer equivalent. The closest Azure service is Azure AI Search, a search engine with vector, hybrid, and keyword search. Azure Blob Storage doesn't offer vector indexes.
- Model. S3 Vectors is storage with built-in similarity queries, billed per use with no cluster. AI Search is a provisioned search service (billed per search unit) with much richer querying, including hybrid search, semantic ranking, filters, and agentic retrieval.
- Latency. S3 Vectors favors cost over speed (subsecond for infrequent queries, as low as about 100 ms for frequent ones). AI Search is built for interactive search latency.
- Integration. S3 Vectors plugs into Bedrock Knowledge Bases and can serve as a lower-cost tier for OpenSearch. AI Search plugs into Microsoft Foundry.
Safety, RAG & search(2)
Managed RAG / knowledge bases Direct match
The Azure equivalent of Amazon Bedrock Knowledge Bases is Foundry IQ knowledge bases, which run on Azure AI Search with agentic retrieval.
- Bedrock offers a Managed Knowledge Base (AWS runs ingestion, storage, and agentic multi-hop retrieval) or customer-managed vector stores (OpenSearch Serverless, Aurora, Neptune Analytics graphs, Kendra GenAI index, structured data stores).
- Foundry IQ is a multi-source knowledge base on Azure AI Search. It covers Blob, SharePoint, OneLake, and web sources, syncs ACLs, honors Microsoft Purview sensitivity labels, and enforces permissions at query time under the caller's Entra identity.
- Foundry IQ is partly GA and partly preview depending on the Search REST API version. Bedrock Knowledge Bases is GA.
Enterprise / intelligent search Partial match
Amazon Kendra maps to Azure AI Search, but Kendra is in maintenance mode (no new customers since July 30, 2026), and AWS now points new search workloads to Bedrock Managed Knowledge Base.
- Kendra is a turnkey search service (connectors, FAQs, relevance tuning). Azure AI Search is a more general engine. You build indexes with indexers, skillsets, and integrated vectorization, and you get full-text, vector, and hybrid search plus semantic reranking.
- For log analytics or OpenSearch-style workloads, Azure AI Search isn't a replacement (per Microsoft's AWS comparison guide).
- Migration note. AWS's Kendra-to-Bedrock-Managed-KB guide lists feature gaps and workarounds.