Logging · head to head
Checkly vs Dataiku

Checkly
Logging
Active reliability platform combining uptime monitoring, API testing, and incident response
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Checkly free tier has limited check allocations per month; Dataiku no pricing is published at any tier, and the plans page carries no figures at all
- They diverge on capability: Checkly covers Uptime monitoring, Dataiku covers Visual data prep.
Where they differ
Only the attributes on which Checkly and Dataiku actually diverge.
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 Checkly
- Uptime monitoring
- Synthetic browser testing
- API monitoring
- Heartbeat monitoring
- Monitoring-as-Code
- Status pages
- Root cause analysis
- Global locations
Only in Dataiku
- Visual data prep
- AutoML
- MLOps
- Collaboration
- Governence
- Python
- R
- Spark
What people use each for
The jobs each tool is most often brought in to do.
Checkly
- Monitor API endpoints with custom assertionsnot Dataiku
- Test user journeys with browser automationnot Dataiku
- Detect performance degradation across regionsnot Dataiku
- Verify DNS and TCP connectivitynot Dataiku
- Ensure cron jobs and background tasks completenot Dataiku
Dataiku
- Building and deploying data science and machine learning pipelinesnot Checkly
- Giving analysts and data scientists a shared visual and code environmentnot Checkly
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Checkly
- Free tier has limited check allocations per month
- Overage charges can add up with high-volume workloads
- Status pages require separate paid tier
- Root cause analysis is separate billing component
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
Pricing, plan by plan
Checkly
Free- HobbyFree
- 10 uptime monitors
- 1,000 browser checks monthly
- 10,000 API checks monthly
- Team$64/month
- 75 uptime monitors
- 12,000 browser checks monthly
- 100,000 API checks monthly
- Enterprise$undefined/custom
- Custom monitor quantities
- All 22 global locations
- 1-second check frequency
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
Which should you pick?
Choose Checkly if
- You need uptime monitoring.
- You want to start without paying.
- You work on Web, CLI, API.
- You also want synthetic browser testing.
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.
Questions people ask
- Is Checkly or Dataiku better?
- Neither clearly leads. Checkly starts at Free and Dataiku at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Checkly or Dataiku?
- Checkly starts at Free and Dataiku at Free.
- Does Checkly or Dataiku run on more platforms?
- Checkly runs on Web, CLI, API. Dataiku runs on Linux, Mac, Windows, Web.
- Can I use Checkly for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Checkly best used for?
- Checkly is most often used for monitor api endpoints with custom assertions, test user journeys with browser automation, detect performance degradation across regions, verify dns and tcp connectivity. Of those, monitor api endpoints with custom assertions and test user journeys with browser automation are not what Dataiku is typically brought in for.
- What can Checkly do that Dataiku cannot?
- Checkly covers Uptime monitoring, Synthetic browser testing, API monitoring, Heartbeat monitoring. Dataiku covers Visual data prep, AutoML, MLOps, Collaboration.
Answered from the vendors’ own pages
Checkly: What is included in the free Checkly plan?
The free Hobby plan includes 10 uptime monitors, 1,000 monthly browser checks, 10,000 monthly API checks, 6 monitoring locations, and 2-minute minimum check frequency with email, Slack, and webhook alerts.
SourceDataiku: 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.
SourceCheckly: Can I write monitoring checks in my preferred language?
Yes, Checkly uses TypeScript/JavaScript for monitoring-as-code, integrated with Playwright for browser testing and supporting REST API testing.
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.
SourceCheckly: How much does status page add to my bill?
Status pages cost between $0-$30/month depending on your plan tier, billed separately from core monitoring.
SourceCheckly: What is the minimum check frequency?
The Hobby and Starter plans support 2-minute and 1-minute minimums respectively. The Team plan supports 30-second intervals, while Enterprise offers 1-second minimum frequency.
SourceRelated pages
Other head to heads
- Checkly vs Elastic Stack
- Checkly vs New Relic
- Checkly vs Datadog Logs
- Checkly vs Coralogix
- Checkly vs Grafana Loki
- Checkly vs incident.io
- Checkly vs Cronitor
- Checkly vs FireHydrant
- Checkly vs Healthchecks
- Checkly vs Openstatus
- Checkly vs Rootly
- Checkly vs CloudWatch
- Checkly vs Dynatrace
- Checkly vs InfluxDB
- Checkly vs Airbrake
- Checkly vs AppDynamics
- Checkly vs Axiom
- Checkly vs Azure Monitor
- Checkly vs AWS SageMaker
- Checkly vs Google Vertex AI
- Checkly vs Azure Machine Learning
- Checkly vs DataRobot
- Checkly vs MLflow
- Checkly vs Snowflake
- Checkly vs TensorFlow
- Checkly vs Comet ML
- Checkly vs Jupyter
- Checkly vs LangChain
- Checkly vs Pinecone
- Checkly vs Python
- Checkly vs PyTorch
- Checkly vs scikit-learn
- Checkly vs Apache Spark MLlib
- Checkly vs Weaviate
- Checkly vs Weights & Biases
- Checkly 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 Rootly
- Dataiku vs CloudWatch
- Dataiku vs Dynatrace
- Dataiku vs InfluxDB
- Dataiku vs Airbrake
- Dataiku vs AppDynamics
- Dataiku vs Axiom
- Dataiku vs Azure Monitor
- 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

