Softwr

Software · head to head

AWS SageMaker vs Greenhouse

AWS SageMaker logo

AWS SageMaker

Software

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite
Greenhouse logo

Greenhouse

Software

Hiring software for growing companies

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; Greenhouse core plan lacks talent discovery and contact lookups
  • They diverge on capability: AWS SageMaker covers Jupyter notebooks, Greenhouse covers Applicant tracking.

Where they differ

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

Attributes where AWS SageMaker and Greenhouse differ
AttributeAWS SageMakerGreenhouse
Starting priceFreeOn request
Pricing modelUnknownquote
Free tierYesNo
PlatformsWebWeb, Ios, Android, Api
Founded20062012

Identical on both: 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 Greenhouse

  • Applicant tracking
  • Interview scheduling
  • Scorecard system
  • Job board posting
  • Candidate CRM
  • Reporting & analytics
  • Offer management
  • EEO compliance

What people use each for

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

AWS SageMaker

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

Greenhouse

  • Applicant tracking system for structured hiringnot AWS SageMaker
  • AI-powered interview notetaking and sourcingnot 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

Greenhouse

  • Core plan lacks talent discovery and contact lookups
  • Core plan lacks email automation and applicant texting
  • Plus plan lacks resume anonymisation and application limits
  • Plus plan lacks audit logging and developer tools
  • Pricing customised by hiring volume and company size, not published
  • Only Pro tier offers audit logs and developer sandbox

Pricing, plan by plan

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

Greenhouse

On request

No published plan breakdown. See the Greenhouse 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 Greenhouse if

  • You need applicant tracking.
  • You work on Web, Ios, Android, Api.
  • You also want interview scheduling.
Greenhouse review

Questions people ask

Is AWS SageMaker or Greenhouse better?
Neither clearly leads. AWS SageMaker starts at Free and Greenhouse at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS SageMaker or Greenhouse?
AWS SageMaker has a free tier; the other does not. Paid plans start at Free for AWS SageMaker and On request for Greenhouse.
Does AWS SageMaker or Greenhouse run on more platforms?
AWS SageMaker runs on Web. Greenhouse runs on Web, Ios, Android, Api.
Can I use AWS SageMaker for free?
Yes. AWS SageMaker has a free tier, so you can try it without paying. Greenhouse 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 Greenhouse is typically brought in for.
What can AWS SageMaker do that Greenhouse cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Greenhouse covers Applicant tracking, Interview scheduling, Scorecard system, Job board posting.

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
ShareXLinkedInRedditWhatsAppEmail

Related pages

More on AWS SageMaker

More on Greenhouse

Keep looking

Other head to heads