Amazon SageMaker
AWS's fully managed platform to build, train, and deploy ML models at scale
Amazon Web Services · Platforms
Launched Nov 29, 2017
Quick Answer
Amazon SageMaker is aws's fully managed platform to build, train, and deploy ml models at scale, made by Amazon Web Services. It is a paid product. Key uses: Enterprise ML model development, Foundation model fine-tuning, Batch ML inference.
Last updated:
Users
Hundreds of thousands of enterprises; $110B+ AWS investment
Valuation
Part of Amazon ($2T+ market cap)
What is Amazon SageMaker?
Amazon SageMaker is a fully managed machine learning service that covers the complete ML lifecycle: data labeling, feature engineering, model training, hyperparameter tuning, model evaluation, deployment, and monitoring. SageMaker JumpStart provides one-click access to hundreds of foundation models including Llama, Falcon, and Stable Diffusion.
What's new in Amazon SageMaker in 2026?
SageMaker Unified Studio (2024) — merged SageMaker + Glue + Redshift tooling; SageMaker JumpStart now has 800+ foundation models; SageMaker HyperPod for large-scale training; integration with Amazon Bedrock; SageMaker Canvas no-code ML; Amazon Q developer integration; $110B AWS infrastructure investment 2025
How much does Amazon SageMaker cost?
Notebooks
From $0.05/hr (t2.medium)
- SageMaker Studio notebooks
- Managed Jupyter
- S3 integration
Training
From $0.126/hr (ml.m5.large)
- Distributed training
- Spot instance savings
- Hyperparameter tuning
Inference
From $0.05/hr (ml.t2.medium)
- Real-time endpoints
- Serverless inference
- Batch transform
What can you do with Amazon SageMaker?
- Enterprise ML model development
- Foundation model fine-tuning
- Batch ML inference
- ML experiment management
- Production ML deployment
Pros
- Deep AWS integration
- Comprehensive end-to-end platform
- SageMaker JumpStart (foundation models)
- Auto-scaling
- Managed notebooks
Cons
- Complex pricing
- Steep learning curve
- AWS vendor lock-in
- Can be expensive
What are the best alternatives to Amazon SageMaker?
Compare Amazon SageMaker Head-to-Head
Frequently Asked Questions about Amazon SageMaker
How much does Amazon SageMaker cost?
Amazon SageMaker pricing: Notebooks at From $0.05/hr (t2.medium); Training at From $0.126/hr (ml.m5.large); Inference at From $0.05/hr (ml.t2.medium).
Is Amazon SageMaker free?
Amazon SageMaker is a paid product with no permanent free tier.
What is Amazon SageMaker used for?
Amazon SageMaker is used for: Enterprise ML model development, Foundation model fine-tuning, Batch ML inference, ML experiment management, Production ML deployment.
What are the best alternatives to Amazon SageMaker?
Top alternatives to Amazon SageMaker include Databricks, Amazon Bedrock, Google Vertex AI.
What platforms does Amazon SageMaker support?
Amazon SageMaker is available on: AWS Console, SageMaker Studio, Python SDK.
Details
Vendor
Amazon Web Services
Category
Platforms
Pricing Model
Launched
Nov 29, 2017
Website
aws.amazon.com/sagemakerUnderlying Models
Platforms
Integrations
Ideal For
- Enterprise ML teams
- Data scientists at AWS-centric companies
- Large-scale model training
- Regulated industries