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Software · head to head

AWS SageMaker vs Fibery

AWS SageMaker logo

AWS SageMaker

Software

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite
Fibery logo

Fibery

Software

Connected workspace for product teams

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; Fibery free plan limited to 10 users and 10 guests
  • They diverge on capability: AWS SageMaker covers Jupyter notebooks, Fibery covers Customizable databases.

Where they differ

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

Attributes where AWS SageMaker and Fibery differ
AttributeAWS SageMakerFibery
Pricing modelUnknownsubscription
Founded20062018

Identical on both: starting price (Free), free tier (Yes), platforms (Web), 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 Fibery

  • Customizable databases
  • Bi-directional linking
  • Whiteboards
  • Documents
  • Timelines
  • Formulas
  • Automations
  • API access

Both cover

  • Web support

What people use each for

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

AWS SageMaker

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

Fibery

  • Work management and product development platformnot AWS SageMaker
  • Relational database with multiple view types (table, board, gallery, timeline, calendar, Gantt)not AWS SageMaker
  • Knowledge base and document collaborationnot 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

Fibery

  • Free plan limited to 10 users and 10 guests
  • Free plan limited to 10 databases
  • Enterprise plan requires minimum of 25 paid users
  • SAML SSO available only on Enterprise plan

Pricing, plan by plan

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

Fibery

Free

No published plan breakdown. See the Fibery 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 Fibery if

  • You need customizable databases.
  • You want to start without paying.
  • You also want bi-directional linking.
Fibery review

Questions people ask

Is AWS SageMaker or Fibery better?
Neither clearly leads. AWS SageMaker starts at Free and Fibery at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS SageMaker or Fibery?
AWS SageMaker starts at Free and Fibery at Free.
Does AWS SageMaker or Fibery run on more platforms?
Both run on Web, so platform support will not decide this one for you.
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 Fibery is typically brought in for.
What can AWS SageMaker do that Fibery cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Fibery covers Customizable databases, Bi-directional linking, Whiteboards, Documents. 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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Related pages

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