Safety, RAG & search · AWS vs Google Cloud
Amazon Bedrock Knowledge Bases vs RAG Engine / Vector Search
Bedrock Knowledge Bases maps to RAG Engine on Agent Platform, which ingests, chunks, embeds, and retrieves your data, using a managed Spanner-backed database or Vector Search and other vector stores.
Side-by-side comparison
| Aspect | Amazon Web Services | Google Cloud |
|---|---|---|
| Service | Amazon Bedrock Knowledge Bases | RAG Engine Vector Search |
| Lifecycle | Generally available | Generally available Generally available |
| What it is | Managed RAG. Managed Knowledge Base (AWS runs ingestion, storage, and agentic retrieval) or customer-managed (bring your own vector store, such as OpenSearch Serverless, Aurora, or Neptune). | Managed retrieval-augmented generation that ingests, chunks, embeds, and retrieves your data, with a managed or bring-your-own vector database. Managed approximate-nearest-neighbor vector search built on Google's ScaNN algorithm. |
| Pricing model | Managed KB is billed on ingested size, query volume, and LLM usage. Customer-managed KBs bill for the underlying vector store plus embedding and generation tokens. | Billed for embedding and generation model calls and for the vector store you use (managed Spanner or Vector Search node-hours). |
| Docs | Amazon Bedrock Knowledge Bases docs | RAG Engine docs Vector Search docs |
| Pricing page | Amazon Bedrock Knowledge Bases pricing | RAG Engine pricing Vector Search pricing |
Key differences
- RAG Engine needs allowlisting in some regions for new projects (us-central1, us-east1, us-east4, europe-west1 per the docs).
- If you use the RAG Engine-managed Spanner instance, that Spanner instance is billed to you.
- For managed search with connectors and ranking out of the box, Agent Search is the alternative.
Pricing summary
Pricing models only. No prices are quoted because they change by region and over time.
- AWS
- Managed KB is billed on ingested size, query volume, and LLM usage. Customer-managed KBs bill for the underlying vector store plus embedding and generation tokens. Amazon Bedrock Knowledge Bases pricing →
- GCP
- Billed for embedding and generation model calls and for the vector store you use (managed Spanner or Vector Search node-hours). RAG Engine pricing → Vector Search pricing →
And on Azure?
Direct match Azure's equivalent is Foundry IQ (knowledge bases), Azure AI Search. AWS vs Azure comparison →
FAQ
What is the Google Cloud equivalent of Amazon Bedrock Knowledge Bases?
Bedrock Knowledge Bases maps to RAG Engine on Agent Platform, which ingests, chunks, embeds, and retrieves your data, using a managed Spanner-backed database or Vector Search and other vector stores.
How does pricing compare between Amazon Bedrock Knowledge Bases and RAG Engine and Vector Search?
AWS: Managed KB is billed on ingested size, query volume, and LLM usage. Customer-managed KBs bill for the underlying vector store plus embedding and generation tokens. Google Cloud: Billed for embedding and generation model calls and for the vector store you use (managed Spanner or Vector Search node-hours). Check the official pricing pages for current rates.
What is the Azure equivalent?
Foundry IQ (knowledge bases) and Azure AI Search (direct match). The Azure equivalent of Amazon Bedrock Knowledge Bases is Foundry IQ knowledge bases, which run on Azure AI Search with agentic retrieval.