Skip to main content

Amazon Bedrock and Amazon SageMaker AI

Compare Amazon Bedrock and Amazon SageMaker AI: features, pricing, and use cases.

Compare side-by-side

Comparisons
Amazon Bedrock
Amazon SageMaker AI
Category

Artificial Intelligence, Foundation model platform

Artificial Intelligence, ML platform
Description

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

A fully managed service to build, train, and deploy machine learning models
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 AI 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 AI 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 AI »

When to use Amazon Bedrock or Amazon SageMaker AI

Use Amazon Bedrock when:

  • Generative AI apps
  • Text generation
  • Chatbots
  • Image generation
  • RAG applications

Learn more about Amazon Bedrock »

Use Amazon SageMaker AI when:

  • ML model training
  • MLOps
  • Computer vision
  • NLP
  • Predictive analytics

Learn more about Amazon SageMaker AI »

AWS product comparisons

Read about AWS products side-by-side

Displaying 1-8 (21)
2026-07-30

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.
Learn more
2026-07-30

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.
Learn more
2026-07-30

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.
Learn more
2026-07-30

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.
Learn more
2026-07-30

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.
Learn more
2026-07-30

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.
Learn more
2026-07-30

What's the difference between Amazon ElastiCache and Amazon MemoryDB?

Both are Redis-compatible, fully managed in-memory services on AWS. ElastiCache is designed as a caching layer in front of another database; MemoryDB is designed as a primary database that combines in-memory speed with Multi-AZ durability.
Learn more
2026-07-30

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.
Learn more

Did you find what you were looking for today?

Let us know so we can improve the quality of the content on our pages