What's the Difference Between Amazon Bedrock and Amazon SageMaker?

Compare Amazon Bedrock and Amazon SageMaker side by side — features, pricing, and ideal use cases to help you choose the right product.

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Compare side-by-side

Comparisons	Amazon Bedrock	Amazon SageMaker
Category	Artificial Intelligence, Foundation model platform	Artificial Intelligence, ML platform
Description	The end-to-end platform for building generative AI applications and agents	The center for all your data, analytics, and AI
Best for	Generative AI apps Text generation Chatbots Image generation RAG applications	ML model training MLOps Computer vision NLP Predictive analytics
Key features	Multiple foundation models Knowledge Bases Agents Guardrails Fine-tuning	SageMaker Studio Built-in algorithms AutoML Model monitoring Feature Store
Pricing model	Pay per input/output token or provisioned throughput	Pay for ML instances + storage + data processing
Free tier	No	Yes
Expert take	“Bedrock is the fastest path to production generative AI. You get access to models from Anthropic, Meta, Mistral, and Amazon without managing infrastructure. Knowledge Bases handle RAG, Guardrails enforce content policies, and Agents chain tool calls; all serverless.” — Oleksii Bebych, re:Post Top Contributor [profile]	“SageMaker is for teams that need full control over training and deployment. You pick the algorithm, data, instance type, and hyperparameters. The trade-off versus Bedrock is complexity for flexibility: SageMaker lets you fine-tune any model, not just foundation models.” — Riku Kobayashi, re:Post Top Contributor [profile]
Product page	Learn more about Amazon Bedrock »	Learn more about Amazon SageMaker »

When to use Amazon Bedrock or Amazon SageMaker

Use Amazon Bedrock when:

Generative AI apps
Text generation
Chatbots
Image generation
RAG applications

Learn more about Amazon Bedrock »

Use Amazon SageMaker when:

ML model training
MLOps
Computer vision
NLP
Predictive analytics

Learn more about Amazon SageMaker »

Next steps with AWS for Artificial Intelligence

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Start building with Amazon Bedrock and Amazon SageMaker on the AWS Free Tier.

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The end-to-end platform for building generative AI applications and agents

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Get started with Amazon SageMaker

The center for all your data, analytics, and AI

Go to Amazon SageMaker

AWS product comparisons

What's the difference between Amazon Aurora and Amazon RDS?

Both are fully managed relational database services on AWS, but Aurora is a cloud-native engine built for higher performance and availability, while RDS gives you familiar open-source and commercial engines with less operational overhead than self-managed.

What's the difference between Amazon DynamoDB and Amazon RDS?

DynamoDB is a serverless NoSQL database for applications with well-defined access patterns that need consistent single-digit millisecond performance. RDS is a managed relational database for applications that need SQL, joins, and transactional integrity across multiple engines.

What's the difference between Amazon DynamoDB and Amazon Keyspaces?

Both are fully managed, serverless-capable NoSQL databases on AWS. DynamoDB is AWS-native with its own API and data model; Keyspaces is Apache Cassandra-compatible, letting you use existing Cassandra drivers, tools, and expertise.

What are the differences between Amazon DynamoDB and Amazon DocumentDB?

Both are fully managed NoSQL databases on AWS, but they serve different data models. DynamoDB is a key-value store optimized for known access patterns at massive scale; DocumentDB is a document database for flexible JSON schemas with MongoDB compatibility.

What's the difference between Amazon DocumentDB and Amazon Neptune?

Both handle semi-structured data, but they're optimized for different query patterns. DocumentDB stores and queries JSON documents; Neptune stores and traverses relationships between entities.

What's the difference between Amazon Aurora and Amazon RDS?

Both are fully managed relational database services on AWS, but Aurora is a cloud-native engine built for higher performance and availability, while RDS gives you familiar open-source and commercial engines with less operational overhead than self-managed.

What's the difference between Amazon Aurora and Amazon Neptune?

Both are purpose-built, fully managed AWS databases, but they solve fundamentally different problems. Aurora handles structured relational data with SQL; Neptune handles highly connected data where relationships between entities are the primary query pattern.

What's the difference between Amazon Aurora and Amazon DynamoDB?

Both are fully managed AWS database services, but they serve fundamentally different data models and access patterns. Aurora is a relational database for structured data with relationships; DynamoDB is a NoSQL key-value store built for single-digit millisecond performance at any scale.

What's the difference between Amazon RDS and Amazon Redshift?

Both run SQL queries, but they're optimized for fundamentally different workloads. RDS handles transactional operations (inserts, updates, lookups) for your application. Redshift handles analytical queries (aggregations, scans, joins across billions of rows) for your data team.

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