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Machine Learning · head to head

AWS SageMaker vs DeepSource

AWS SageMaker logo

AWS SageMaker

Machine Learning

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite
DeepSource logo

DeepSource

Software Development

Automated code review and AI-powered code fixes for engineering 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; DeepSource open Source plan caps at 1,000 reviewed pull requests and 1,000 formatting runs per month.
  • They diverge on capability: AWS SageMaker covers Jupyter notebooks, DeepSource covers Automated pull request review.

Where they differ

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

Attributes where AWS SageMaker and DeepSource differ
AttributeAWS SageMakerDeepSource
Pricing modelUnknownfreemium
PlatformsWebweb, api
CategoryMachine LearningSoftware Development
Founded2006Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

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 DeepSource

  • Automated pull request review
  • AI-powered autofix
  • Automated code formatting
  • Monorepo support
  • API and webhooks
  • Bring-your-own-key AI

What people use each for

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

AWS SageMaker

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

DeepSource

  • Automating pull request code review for engineering teamsnot AWS SageMaker
  • Auto-fixing detected code issues with AInot AWS SageMaker
  • Enforcing code formatting standards automaticallynot AWS SageMaker
  • Scanning large monorepos for quality issuesnot AWS SageMaker
  • Running self-hosted AI review in regulated environmentsnot 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

DeepSource

  • Open Source plan caps at 1,000 reviewed pull requests and 1,000 formatting runs per month.
  • AI Review beyond the included credit is billed per 10K lines of code, which can add unpredictable cost.
  • Self-hosted deployment and BYOK AI are Enterprise-only features.
  • Enterprise pricing is not published and requires contacting sales.

Pricing, plan by plan

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

DeepSource

Free
  • Open SourceFree
    • Free for public repositories
    • 1,000 pull requests reviewed/month
    • 1,000 automated formatting runs/month
  • Team$24/month
    • Unlimited repositories and pull request reviews
    • $100 annual AI Review credit per user
    • Monorepo support
  • Enterprise$undefined/month
    • Self-hosted deployment
    • Bring-your-own-key AI Review
    • SSO

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 DeepSource if

  • You need automated pull request review.
  • You want to start without paying.
  • You work on web, api.
  • You also want ai-powered autofix.
DeepSource review

Questions people ask

Is AWS SageMaker or DeepSource better?
Neither clearly leads. AWS SageMaker starts at Free and DeepSource at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS SageMaker or DeepSource?
AWS SageMaker starts at Free and DeepSource at Free.
Does AWS SageMaker or DeepSource run on more platforms?
AWS SageMaker runs on Web. DeepSource runs on web, api.
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 DeepSource is typically brought in for.
What can AWS SageMaker do that DeepSource cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. DeepSource covers Automated pull request review, AI-powered autofix, Automated code formatting, Monorepo 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
DeepSource: What does DeepSource cost?

The Open Source plan is free for public repos; Team is $24 per user/month billed yearly with a $100 annual AI Review credit; Enterprise is custom-priced with self-hosted options.

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
DeepSource: Is there a free plan, and what are its limits?

Yes, the free Open Source plan covers public repositories with 1,000 pull requests reviewed per month and 1,000 automated formatting runs per month.

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
DeepSource: How is AI Review usage metered?

Team plans include a $100 annual AI Review credit per user, with additional usage billed at Standard ($8/10K LOC) or Advanced ($15/10K LOC) tiers.

Source
DeepSource: Can I change or cancel my plan?

Yes, subscriptions can be downgraded or canceled at any time.

Source
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