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Machine Learning & Data Science · head to head

AWS SageMaker vs Metabase

AWS SageMaker logo

AWS SageMaker

Machine Learning & Data Science

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite
Metabase logo

Metabase

Spreadsheet & Data

Fast analytics with the friendly UX

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; Metabase row and column level permissions and SSO available only in Pro tier and above
  • They diverge on capability: AWS SageMaker covers Jupyter notebooks, Metabase covers No-code Query Builder.

Where they differ

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

Attributes where AWS SageMaker and Metabase differ
AttributeAWS SageMakerMetabase
PlatformsWebWeb, Self-hosted cloud
CategoryMachine Learning & Data ScienceSpreadsheet & Data
Founded20062014

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

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 Metabase

  • No-code Query Builder
  • SQL Editor
  • Interactive Dashboards
  • Alerts
  • Embedding
  • PostgreSQL
  • MySQL
  • MongoDB

Both cover

  • Web support

What people use each for

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

AWS SageMaker

  • Machine learningnot Metabase
  • Data analysisnot Metabase
  • Model trainingnot Metabase
  • Predictive analyticsnot Metabase

Metabase

  • Business intelligence and data exploration for non-technical usersnot AWS SageMaker
  • Embedded analytics for SaaS applicationsnot AWS SageMaker
  • Self-service reporting and dashboard creationnot AWS SageMaker
  • Integration with 40+ data sources including cloud warehousesnot AWS SageMaker

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

Metabase

  • Row and column level permissions and SSO available only in Pro tier and above
  • Advanced analytics features like multi-tenant embedded analytics require Pro tier or higher
  • AI-powered features incur additional usage-based costs: $3.75 per 1M tokens
  • Self-hosted deployment on Free/Open Source tier requires infrastructure management

Pricing, plan by plan

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

Metabase

Free

No published plan breakdown. See the Metabase review.

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 Metabase if

  • You need no-code query builder.
  • You want to start without paying.
  • You work on Web, Self-hosted cloud.
  • You also want sql editor.
Metabase review

Questions people ask

Is AWS SageMaker or Metabase better?
Neither clearly leads. AWS SageMaker starts at Free and Metabase at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS SageMaker or Metabase?
AWS SageMaker starts at Free and Metabase at Free.
Does AWS SageMaker or Metabase run on more platforms?
AWS SageMaker runs on Web. Metabase runs on Web, Self-hosted cloud.
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. Of those, machine learning and data analysis are not what Metabase is typically brought in for.
What can AWS SageMaker do that Metabase cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Metabase covers No-code Query Builder, SQL Editor, Interactive Dashboards, Alerts. Both handle Web 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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