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Software Development · head to head

DeepSource vs Google Vertex AI

DeepSource logo

DeepSource

Software Development

Automated code review and AI-powered code fixes for engineering teams.

From
Free
Rated
-
Full reviewWebsite
Google Vertex AI logo

Google Vertex AI

Machine Learning

Unified ML platform to build, deploy, and scale AI models

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only DeepSource has a free tier, so it costs nothing to try first.
  • Each has a real cost: DeepSource open Source plan caps at 1,000 reviewed pull requests and 1,000 formatting runs per month.; Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • They diverge on capability: DeepSource covers Automated pull request review, Google Vertex AI covers AutoML.

Where they differ

Only the attributes on which DeepSource and Google Vertex AI actually diverge.

Attributes where DeepSource and Google Vertex AI differ
AttributeDeepSourceGoogle Vertex AI
Starting priceFreeOn request
Pricing modelfreemiumUnknown
Free tierYesNo
Platformsweb, apiCloud, Web
CategorySoftware DevelopmentMachine Learning
FoundedUnknown2008

Identical on both: 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 DeepSource

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

Only in Google Vertex AI

  • AutoML
  • Custom training
  • Feature Store
  • Model monitoring
  • Prediction serving
  • BigQuery
  • Cloud Storage
  • TensorFlow

What people use each for

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

DeepSource

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

Google Vertex AI

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

Where each one falls short

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

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.

Google Vertex AI

  • Vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • Requires familiarity with Google Cloud Platform infrastructure and concepts
  • Cost can escalate quickly with large training and inference workloads

Pricing, plan by plan

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

Google Vertex AI

On request

No published plan breakdown. See the Google Vertex AI review.

Which should you pick?

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

Choose Google Vertex AI if

  • You need automl.
  • You work on Cloud, Web.
  • You also want custom training.
Google Vertex AI review

Questions people ask

Is DeepSource or Google Vertex AI better?
Neither clearly leads. DeepSource starts at Free and Google Vertex AI at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DeepSource or Google Vertex AI?
DeepSource has a free tier; the other does not. Paid plans start at Free for DeepSource and On request for Google Vertex AI.
Does DeepSource or Google Vertex AI run on more platforms?
DeepSource runs on web, api. Google Vertex AI runs on Cloud, Web.
Can I use DeepSource for free?
Yes. DeepSource has a free tier, so you can try it without paying. Google Vertex AI starts at On request.
What is DeepSource best used for?
DeepSource is most often used for automating pull request code review for engineering teams, auto-fixing detected code issues with ai, enforcing code formatting standards automatically, scanning large monorepos for quality issues. Of those, automating pull request code review for engineering teams and auto-fixing detected code issues with ai are not what Google Vertex AI is typically brought in for.
What can DeepSource do that Google Vertex AI cannot?
DeepSource covers Automated pull request review, AI-powered autofix, Automated code formatting, Monorepo support. Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring.

Answered from the vendors’ own pages

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
Google Vertex AI: What is the pricing model for Google Vertex AI?

Vertex AI uses a pay-as-you-go model with no upfront costs or lock-in fees. Costs vary by service: training is billed by compute resources and time (30-second increments), online predictions by machine type per hour, and batch predictions by compute time or per-record for specific AutoML types.

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
Google Vertex AI: What types of data can Vertex AI handle?

Vertex AI supports image, video, text, and tabular data types with tools for uploading, storing, and managing large datasets.

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
Google Vertex AI: Does Vertex AI support custom model training?

Yes. Vertex AI supports both AutoML for automated machine learning and custom training code in Python, R, and other languages.

Source
DeepSource: Can I change or cancel my plan?

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

Source
Google Vertex AI: What deployment options are available in Vertex AI?

Vertex AI supports online predictions for real-time use cases and batch predictions for large-scale processing.

Source
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