Software · head to head
Dataiku vs AWS SageMaker
AWS SageMaker
Software
Build, train, and deploy machine learning models at scale
- 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; AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult
- They diverge on capability: Dataiku covers Visual data prep, AWS SageMaker covers Jupyter notebooks.
Where they differ
Only the attributes on which Dataiku and AWS SageMaker actually diverge.
| Attribute | Dataiku | AWS SageMaker |
|---|---|---|
| Pricing model | freemium | Unknown |
| Platforms | Linux, Mac, Windows, Web | Web |
| Founded | 2013 | 2006 |
Identical on both: starting price (Free), free tier (Yes), 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 Dataiku
- Visual data prep
- AutoML
- MLOps
- Collaboration
- Governence
- Python
- R
- Spark
Only in AWS SageMaker
- Jupyter notebooks
- Built-in algorithms
- Automatic model tuning
- One-click deployment
- Model monitoring
- S3
- Lambda
- Step Functions
Both cover
- Web support
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 AWS SageMaker
- Giving analysts and data scientists a shared visual and code environmentnot AWS SageMaker
AWS SageMaker
- Machine learningnot Dataiku
- Data analysisnot Dataiku
- Model trainingnot Dataiku
- Predictive analyticsnot 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
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
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
AWS SageMaker
FreeNo published plan breakdown. See the AWS SageMaker review.
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 AWS SageMaker if
- You need jupyter notebooks.
- You want to start without paying.
- You also want built-in algorithms.
Questions people ask
- Is Dataiku or AWS SageMaker better?
- Neither clearly leads. Dataiku 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, Dataiku or AWS SageMaker?
- Dataiku starts at Free and AWS SageMaker at Free.
- Does Dataiku or AWS SageMaker run on more platforms?
- Dataiku runs on Linux, Mac, Windows, Web. AWS SageMaker runs on Web.
- 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 AWS SageMaker is typically brought in for.
- What can Dataiku do that AWS SageMaker cannot?
- Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Both handle Web 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.
SourceAWS 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.
SourceAWS 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