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AWS SageMaker vs BentoML

AWS SageMaker logo

AWS SageMaker

Software

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite
BentoML logo

BentoML

Software

Build production-ready ML applications

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult; BentoML core BentoML framework is Apache 2.0 and free, but the managed BentoCloud enterprise tier has no published pricing: the README instructs buyers to sign up for personal access or contact sales for enterprise use, with no rate card shown.
  • They diverge on capability: AWS SageMaker covers Jupyter notebooks, BentoML covers Model packaging.

Where they differ

Only the attributes on which AWS SageMaker and BentoML actually diverge.

Attributes where AWS SageMaker and BentoML differ
AttributeAWS SageMakerBentoML
Pricing modelUnknownfreemium
PlatformsWebLinux, Mac, Windows
Founded20062019

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in AWS SageMaker

  • Jupyter notebooks
  • Built-in algorithms
  • Automatic model tuning
  • One-click deployment
  • Model monitoring
  • S3
  • Lambda
  • Step Functions

Only in BentoML

  • Model packaging
  • REST API generation
  • Adaptive batching
  • Multi-framework support
  • Container deployment
  • PyTorch
  • TensorFlow
  • scikit-learn

What people use each for

The jobs each tool is most often brought in to do.

AWS SageMaker

  • Machine learning
  • Data analysis
  • Model training
  • Predictive analytics

BentoML

  • Machine learning
  • Data analysis
  • Model training
  • Predictive analytics

Both are used for machine learning, data analysis, model training, predictive analytics, on those jobs the choice comes down to price and fit rather than capability.

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

AWS SageMaker

  • Vendor lock-in to AWS ecosystem makes migration to other platforms difficult
  • Opaque pricing can lead to unexpected expenses like forgotten EBS volume charges
  • Does not include native job scheduling, requiring Lambda or EventBridge integration

BentoML

  • Core BentoML framework is Apache 2.0 and free, but the managed BentoCloud enterprise tier has no published pricing: the README instructs buyers to sign up for personal access or contact sales for enterprise use, with no rate card shown.

Pricing, plan by plan

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

BentoML

Free
  • Open SourceFree
    • Model packaging
    • API creation
    • Local serving
  • BentoCloudFree
    • Managed deployment
    • Auto-scaling
    • Monitoring

Which should you pick?

Choose AWS SageMaker if

  • You need jupyter notebooks.
  • You want to start without paying.
  • You also want built-in algorithms.
AWS SageMaker review

Choose BentoML if

  • You need model packaging.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want rest api generation.
BentoML review

Questions people ask

Is AWS SageMaker or BentoML better?
Neither clearly leads. AWS SageMaker starts at Free and BentoML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS SageMaker or BentoML?
AWS SageMaker starts at Free and BentoML at Free.
Does AWS SageMaker or BentoML run on more platforms?
AWS SageMaker runs on Web. BentoML runs on Linux, Mac, Windows.
Can I use AWS SageMaker for free?
Both have a free tier, so you can try either at no cost before committing.
What is AWS SageMaker best used for?
AWS SageMaker is most often used for machine learning, data analysis, model training, predictive analytics.
What can AWS SageMaker do that BentoML cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. BentoML covers Model packaging, REST API generation, Adaptive batching, Multi-framework support.

Answered from the vendors’ own pages

AWS SageMaker: What is AWS SageMaker used for?

AWS SageMaker is a machine learning service for building, training, and deploying ML models at scale. It provides tools for data preparation, model training, inference endpoints, and performance optimization.

Source
AWS SageMaker: How is AWS SageMaker priced?

SageMaker uses pay-as-you-go pricing with no upfront costs or long-term commitments. Pricing starts at $0.04 per hour for basic notebook instances and scales based on instance type. ML Savings Plans offer up to 64% off with hourly spend commitments.

Source
AWS SageMaker: Does AWS SageMaker have a free tier?

Yes, the free tier includes 250 hours of notebook usage, 50 hours of training, and 125 hours of hosting on ml.t3.medium instances during the first two months.

Source
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