Machine Learning · head to head
Dataiku vs Rootly

Rootly
Logging
AI-native incident management with automation, on-call, and root cause analysis
- From
- $20/user-month
- Rated
- -
The short version
- Only Dataiku has a free tier, so it costs nothing to try first.
- Each has a real cost: Dataiku no pricing is published at any tier, and the plans page carries no figures at all; Rootly pricing higher than some competitors for basic features
- They diverge on capability: Dataiku covers Visual data prep, Rootly covers AI SRE automation.
Where they differ
Only the attributes on which Dataiku and Rootly actually diverge.
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 Dataiku
- Visual data prep
- AutoML
- MLOps
- Collaboration
- Governence
- Python
- R
- Spark
Only in Rootly
- AI SRE automation
- Alert routing
- On-call management
- Incident response
- Call routing
- AI meeting bot
- Status pages
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 Rootly
- Giving analysts and data scientists a shared visual and code environmentnot Rootly
Rootly
- Automate on-call and incident response workflowsnot Dataiku
- Run root cause analysis with AI assistancenot Dataiku
- Track and improve Mean Time to Mitigation (MTTR)not Dataiku
- Coordinate response across distributed teamsnot Dataiku
- Learn from post-incident retrospectivesnot 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
Rootly
- Pricing higher than some competitors for basic features
- AI SRE features require separate contact-sales engagement
- Learning curve for advanced automation features
- Per-user pricing increases costs as team grows
Pricing, plan by plan
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
Rootly
$20/user-month- Incident Response Essentials$20/user-month
- Response with Slack integration
- @Rootly AI Chat
- AI Similar Incidents detection
- Incident Response Enterprise$undefined/custom
- All Essentials features
- Custom forms and incident types
- Private incidents
- On-Call Essentials$20/user-month
- Alert grouping and routing
- Live call routing (1 phone number)
- Schedules and escalation policies
- On-Call Enterprise$undefined/custom
- All Essentials features
- 5 phone numbers for call routing
- Unlimited schedules
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 Rootly if
- You need ai sre automation.
- You work on Web, Mobile, Slack, Microsoft Teams.
- You also want alert routing.
Questions people ask
- Is Dataiku or Rootly better?
- Neither clearly leads. Dataiku starts at Free and Rootly at $20/user-month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Dataiku or Rootly?
- Dataiku has a free tier; the other does not. Paid plans start at Free for Dataiku and $20/user-month for Rootly.
- Does Dataiku or Rootly run on more platforms?
- Dataiku runs on Linux, Mac, Windows, Web. Rootly runs on Web, Mobile, Slack, Microsoft Teams.
- Can I use Dataiku for free?
- Yes. Dataiku has a free tier, so you can try it without paying. Rootly starts at $20/user-month.
- 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 Rootly is typically brought in for.
- What can Dataiku do that Rootly cannot?
- Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. Rootly covers AI SRE automation, Alert routing, On-call management, Incident response.
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.
SourceRootly: How much does Rootly cost?
Rootly charges $20/user/month for both Incident Response and On-Call Essentials plans. Enterprise plans require contacting sales. Startups under 100 employees with less than $50M raised get up to 50% discount.
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.
SourceRootly: What is Rootly AI SRE?
AI SRE is an advanced feature that provides automated root cause analysis, alert correlation with system changes, impact analysis, and remediation suggestions. Pricing requires contact with sales.
SourceRootly: Does Rootly integrate with Slack?
Yes, Rootly natively integrates with Slack for incident response workflows, allowing teams to manage incidents directly in Slack.
SourceRootly: Are there discounts for small companies?
Yes, startups under 100 employees or less than 25 employees can get special pricing up to 50% discount. Contact Rootly sales for details.
SourceRelated pages
Other head to heads
- Dataiku vs AWS SageMaker
- Dataiku vs Google Vertex AI
- Dataiku vs Azure Machine Learning
- Dataiku vs DataRobot
- Dataiku vs MLflow
- Dataiku vs Snowflake
- Dataiku vs TensorFlow
- Dataiku vs Comet ML
- Dataiku vs Jupyter
- Dataiku vs LangChain
- Dataiku vs Pinecone
- Dataiku vs Python
- Dataiku vs PyTorch
- Dataiku vs scikit-learn
- Dataiku vs Apache Spark MLlib
- Dataiku vs Weaviate
- Dataiku vs Weights & Biases
- Dataiku vs Alteryx
- Dataiku vs Elastic Stack
- Dataiku vs New Relic
- Dataiku vs Datadog Logs
- Dataiku vs Coralogix
- Dataiku vs Grafana Loki
- Dataiku vs incident.io
- Dataiku vs Cronitor
- Dataiku vs FireHydrant
- Dataiku vs Healthchecks
- Dataiku vs Openstatus
- Dataiku vs Checkly
- Dataiku vs CloudWatch
- Dataiku vs Dynatrace
- Dataiku vs InfluxDB
- Dataiku vs Airbrake
- Dataiku vs AppDynamics
- Dataiku vs Axiom
- Dataiku vs Azure Monitor
- Rootly vs AWS SageMaker
- Rootly vs Google Vertex AI
- Rootly vs Azure Machine Learning
- Rootly vs DataRobot
- Rootly vs MLflow
- Rootly vs Snowflake
- Rootly vs TensorFlow
- Rootly vs Comet ML
- Rootly vs Jupyter
- Rootly vs LangChain
- Rootly vs Pinecone
- Rootly vs Python
- Rootly vs PyTorch
- Rootly vs scikit-learn
- Rootly vs Apache Spark MLlib
- Rootly vs Weaviate
- Rootly vs Weights & Biases
- Rootly vs Alteryx
- Rootly vs Elastic Stack
- Rootly vs New Relic
- Rootly vs Datadog Logs
- Rootly vs Coralogix
- Rootly vs Grafana Loki
- Rootly vs incident.io
- Rootly vs Cronitor
- Rootly vs FireHydrant
- Rootly vs Healthchecks
- Rootly vs Openstatus
- Rootly vs Checkly
- Rootly vs CloudWatch
- Rootly vs Dynatrace
- Rootly vs InfluxDB
- Rootly vs Airbrake
- Rootly vs AppDynamics
- Rootly vs Axiom
- Rootly vs Azure Monitor

