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Software · head to head

AWS SageMaker vs Redash

AWS SageMaker logo

AWS SageMaker

Software

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite
Redash logo

Redash

Software

Connect and visualize your data

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; Redash a basic self-hosted deployment needs a minimum of 4GB of RAM, and more RAM and CPU as background workers and API processes grow
  • They diverge on capability: AWS SageMaker covers Jupyter notebooks, Redash covers SQL Query Editor.

Where they differ

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

Attributes where AWS SageMaker and Redash differ
AttributeAWS SageMakerRedash
Pricing modelUnknownfreemium
PlatformsWebWeb, Self-hosted, Cloud
Founded20062013

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 Redash

  • SQL Query Editor
  • Multiple Data Sources
  • Visualizations
  • Dashboards
  • Alerts
  • PostgreSQL
  • MySQL
  • BigQuery

Both cover

  • Web support

What people use each for

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

AWS SageMaker

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

Redash

  • Self-hosted SQL query editor and dashboarding over existing databasesnot AWS SageMaker
  • Sharing scheduled query results with a team without buying a BI licencenot 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

Redash

  • A basic self-hosted deployment needs a minimum of 4GB of RAM, and more RAM and CPU as background workers and API processes grow
  • The official Docker images were not updated for V10, so the documented route is to deploy a V8 instance and then upgrade it
  • Anyone not using a provided cloud image has to configure the environment variables and secrets by hand

Pricing, plan by plan

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

Redash

Free
  • Open SourceFree
    • Full Features
    • Self-hosted
    • Community Support
  • Cloud$49/month
    • Managed Hosting
    • Automatic Updates
    • Support

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 Redash if

  • You need sql query editor.
  • You want to start without paying.
  • You work on Web, Self-hosted, Cloud.
  • You also want multiple data sources.
Redash review

Questions people ask

Is AWS SageMaker or Redash better?
Neither clearly leads. AWS SageMaker starts at Free and Redash at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS SageMaker or Redash?
AWS SageMaker starts at Free and Redash at Free.
Does AWS SageMaker or Redash run on more platforms?
AWS SageMaker runs on Web. Redash 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 Redash is typically brought in for.
What can AWS SageMaker do that Redash cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Redash covers SQL Query Editor, Multiple Data Sources, Visualizations, Dashboards. 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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