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Software · head to head

AWS SageMaker vs Looker

AWS SageMaker logo

AWS SageMaker

Software

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite
Looker logo

Looker

Software

Modern business intelligence platform by Google

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only AWS SageMaker has a free tier, so it costs nothing to try first.
  • Each has a real cost: AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult; Looker requires annual commitment with no month-to-month billing option
  • They diverge on capability: AWS SageMaker covers Jupyter notebooks, Looker covers LookML Data Modeling.

Where they differ

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

Attributes where AWS SageMaker and Looker differ
AttributeAWS SageMakerLooker
Starting priceFreeOn request
Free tierYesNo
PlatformsWebWeb, Cloud (Google Cloud Platform)
Founded20062008

Identical on both: pricing model (Unknown), 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 Looker

  • LookML Data Modeling
  • Embedded Analytics
  • API Access
  • Version Control
  • Data Actions
  • BigQuery
  • Snowflake
  • Redshift

Both cover

  • Web support

What people use each for

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

AWS SageMaker

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

Looker

  • Business intelligence and interactive dashboards for data-driven decision makingnot AWS SageMaker
  • Embedded analytics for integrating BI capabilities into third-party applicationsnot 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

Looker

  • Requires annual commitment with no month-to-month billing option
  • Conversational analytics will incur token overage charges ($3.00 per 1M input tokens, $20.00 per 1M output tokens) after October 1, 2026

Pricing, plan by plan

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

Looker

On request

No published plan breakdown. See the Looker 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 Looker if

  • You need lookml data modeling.
  • You work on Web, Cloud (Google Cloud Platform).
  • You also want embedded analytics.
Looker review

Questions people ask

Is AWS SageMaker or Looker better?
Neither clearly leads. AWS SageMaker starts at Free and Looker at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS SageMaker or Looker?
AWS SageMaker has a free tier; the other does not. Paid plans start at Free for AWS SageMaker and On request for Looker.
Does AWS SageMaker or Looker run on more platforms?
AWS SageMaker runs on Web. Looker runs on Web, Cloud (Google Cloud Platform).
Can I use AWS SageMaker for free?
Yes. AWS SageMaker has a free tier, so you can try it without paying. Looker starts at On request.
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 Looker is typically brought in for.
What can AWS SageMaker do that Looker cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Looker covers LookML Data Modeling, Embedded Analytics, API Access, Version Control. 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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