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Machine Learning & Data Science · head to head

Pachyderm vs AWS SageMaker

P

Pachyderm

Machine Learning & Data Science

Data versioning and pipelines for production ML

From
Free
Rated
-
Full reviewWebsite
AWS SageMaker logo

AWS SageMaker

Machine Learning & Data Science

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Pachyderm core software is Apache-2.0 licensed and free to self-host; AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult
  • They diverge on capability: Pachyderm covers Data versioning, AWS SageMaker covers Jupyter notebooks.

Where they differ

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

Attributes where Pachyderm and AWS SageMaker differ
AttributePachydermAWS SageMaker
Pricing modelfreemiumUnknown
PlatformsLinuxWeb
Founded20142006

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).

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 Pachyderm

  • Data versioning
  • Data-driven pipelines
  • Automatic provenance
  • Kubernetes-native
  • Reproducibility
  • Kubernetes
  • GCS
  • Azure Blob

Only in AWS SageMaker

  • Jupyter notebooks
  • Built-in algorithms
  • Automatic model tuning
  • One-click deployment
  • Model monitoring
  • Lambda
  • Step Functions
  • CloudWatch

Both cover

  • S3

What people use each for

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

Pachyderm

  • Machine learning
  • Data analysis
  • Model training
  • Predictive analytics

AWS SageMaker

  • Machine learning
  • Data analysis
  • Model training
  • Predictive analytics

Both are used for machine learning, data analysis, model training, predictive analytics, on those jobs the choice comes down to price and fit rather than capability.

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Pachyderm

  • Core software is Apache-2.0 licensed and free to self-host

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

Pricing, plan by plan

Pachyderm

Free
  • CommunityFree
    • Core features
    • Community support
  • EnterpriseFree
    • Advanced security
    • Premium support
    • SLAs

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

Which should you pick?

Choose Pachyderm if

  • You need data versioning.
  • You want to start without paying.
  • You work on Linux.
  • You also want data-driven pipelines.
Pachyderm review

Choose AWS SageMaker if

  • You need jupyter notebooks.
  • You want to start without paying.
  • You also want built-in algorithms.
AWS SageMaker review

Questions people ask

Is Pachyderm or AWS SageMaker better?
Neither clearly leads. Pachyderm starts at Free and AWS SageMaker at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Pachyderm or AWS SageMaker?
Pachyderm starts at Free and AWS SageMaker at Free.
Does Pachyderm or AWS SageMaker run on more platforms?
Pachyderm runs on Linux. AWS SageMaker runs on Web.
Can I use Pachyderm for free?
Both have a free tier, so you can try either at no cost before committing.
What is Pachyderm best used for?
Pachyderm is most often used for machine learning, data analysis, model training, predictive analytics.
What can Pachyderm do that AWS SageMaker cannot?
Pachyderm covers Data versioning, Data-driven pipelines, Automatic provenance, Kubernetes-native. AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Both handle S3.

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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