Machine Learning · head to head
Dataiku vs DeepSource

DeepSource
Software Development
Automated code review and AI-powered code fixes for engineering teams.
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Dataiku no pricing is published at any tier, and the plans page carries no figures at all; DeepSource open Source plan caps at 1,000 reviewed pull requests and 1,000 formatting runs per month.
- They diverge on capability: Dataiku covers Visual data prep, DeepSource covers Automated pull request review.
Where they differ
Only the attributes on which Dataiku and DeepSource actually diverge.
| Attribute | Dataiku | DeepSource |
|---|---|---|
| Platforms | Linux, Mac, Windows, Web | web, api |
| Category | Machine Learning | Software Development |
| Founded | 2013 | Unknown |
Identical on both: starting price (Free), pricing model (freemium), 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 Dataiku
- Visual data prep
- AutoML
- MLOps
- Collaboration
- Governence
- Python
- R
- Spark
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.
Dataiku
- Building and deploying data science and machine learning pipelinesnot DeepSource
- Giving analysts and data scientists a shared visual and code environmentnot DeepSource
DeepSource
- Automating pull request code review for engineering teamsnot Dataiku
- Auto-fixing detected code issues with AInot Dataiku
- Enforcing code formatting standards automaticallynot Dataiku
- Scanning large monorepos for quality issuesnot Dataiku
- Running self-hosted AI review in regulated environmentsnot Dataiku
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Dataiku
- No pricing is published at any tier, and the plans page carries no figures at all
- User, row and compute limits are not stated, so nothing about scale can be assessed before contacting sales
- Access begins with a demo request or a trial rather than a self serve signup
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
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
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 Dataiku if
- You need visual data prep.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want automl.
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.
Questions people ask
- Is Dataiku or DeepSource better?
- Neither clearly leads. Dataiku 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, Dataiku or DeepSource?
- Dataiku starts at Free and DeepSource at Free.
- Does Dataiku or DeepSource run on more platforms?
- Dataiku runs on Linux, Mac, Windows, Web. DeepSource runs on web, api.
- Can I use Dataiku for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Dataiku best used for?
- Dataiku is most often used for building and deploying data science and machine learning pipelines, giving analysts and data scientists a shared visual and code environment. Of those, building and deploying data science and machine learning pipelines and giving analysts and data scientists a shared visual and code environment are not what DeepSource is typically brought in for.
- What can Dataiku do that DeepSource cannot?
- Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. DeepSource covers Automated pull request review, AI-powered autofix, Automated code formatting, Monorepo support.
Answered from the vendors’ own pages
Dataiku: What are Dataiku pricing tiers and costs?
Dataiku pricing information is not available on their public website. Customers must contact Dataiku sales directly to request pricing, trial access, and licensing information.
SourceDeepSource: 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.
SourceDataiku: Does Dataiku offer a free tier or trial?
Free tier or trial availability for Dataiku cannot be determined from publicly accessible pages. Contact Dataiku directly to inquire about evaluation options.
SourceDeepSource: 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.
SourceDeepSource: 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.
SourceDeepSource: Can I change or cancel my plan?
Yes, subscriptions can be downgraded or canceled at any time.
SourceRelated pages
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- Dataiku vs Augment Code
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- Dataiku vs Flagsmith
- Dataiku vs Unleash
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- Dataiku vs Cline
- Dataiku vs Factory
- Dataiku vs Humanloop
- Dataiku vs Langfuse
- DeepSource vs AWS SageMaker
- DeepSource vs Google Vertex AI
- DeepSource vs Azure Machine Learning
- DeepSource vs DataRobot
- DeepSource vs MLflow
- DeepSource vs Snowflake
- DeepSource vs TensorFlow
- DeepSource vs Comet ML
- DeepSource vs Jupyter
- DeepSource vs LangChain
- DeepSource vs Pinecone
- DeepSource vs Python
- DeepSource vs PyTorch
- DeepSource vs scikit-learn
- DeepSource vs Apache Spark MLlib
- DeepSource vs Weaviate
- DeepSource vs Weights & Biases
- DeepSource vs Alteryx
- DeepSource vs Cursor
- DeepSource vs Windsurf
- DeepSource vs Zed
- DeepSource vs Amp
- DeepSource vs Braintrust
- DeepSource vs Codacy
- DeepSource vs Devin
- DeepSource vs SonarQube Cloud
- DeepSource vs Augment Code
- DeepSource vs Baseten
- DeepSource vs Drizzle ORM
- DeepSource vs Flagsmith
- DeepSource vs Unleash
- DeepSource vs Bun
- DeepSource vs Cline
- DeepSource vs Factory
- DeepSource vs Humanloop
- DeepSource vs Langfuse

