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Machine Learning · head to head

Dataiku vs Traceloop

Dataiku logo

Dataiku

Machine Learning

Everyday AI, Extraordinary People

From
Free
Rated
-
Full reviewWebsite
Traceloop logo

Traceloop

Logging

LLM reliability platform with open-source observability and evaluation

From
Free
Rated
-
Full reviewWebsite

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; Traceloop free tier limited to 50k spans per month and 24-hour retention, restricting production use
  • They diverge on capability: Dataiku covers Visual data prep, Traceloop covers Open-source SDK (OpenLLMetry).

Where they differ

Only the attributes on which Dataiku and Traceloop actually diverge.

Attributes where Dataiku and Traceloop differ
AttributeDataikuTraceloop
Pricing modelfreemiumFreemium with pay-as-you-go enterprise option
PlatformsLinux, Mac, Windows, WebCloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby
CategoryMachine LearningLogging
Founded2013Unknown

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 Dataiku

  • Visual data prep
  • AutoML
  • MLOps
  • Collaboration
  • Governence
  • Python
  • R
  • Spark

Only in Traceloop

  • Open-source SDK (OpenLLMetry)
  • Multi-provider support
  • Observability platform integration
  • Framework support
  • Monitoring dashboard
  • Evaluation system
  • Deployment flexibility

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 Traceloop
  • Giving analysts and data scientists a shared visual and code environmentnot Traceloop

Traceloop

  • Monitoring LLM application performance in productionnot Dataiku
  • Instrumenting LLM apps with minimal code overheadnot Dataiku
  • Continuous evaluation and quality scoring of LLM outputsnot Dataiku
  • Debugging LLM application issues with full trace visibilitynot Dataiku
  • Integrating observability data into existing monitoring stacksnot 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

Traceloop

  • Free tier limited to 50k spans per month and 24-hour retention, restricting production use
  • Company acquisition by ServiceNow creates uncertainty about future roadmap
  • Requires integration with separate observability platforms for visualization
  • Less feature-rich than dedicated LLM evaluation platforms

Pricing, plan by plan

Dataiku

Free
  • Free EditionFree
    • Single user
    • Core features
  • EnterpriseFree
    • Full platform
    • Collaboration
    • MLOps

Traceloop

Free
  • FreeFree
    • 50,000 spans per month
    • Up to 5 seats
    • 24-hour data retention
  • Enterprise$undefined/custom
    • Unlimited spans per month
    • Unlimited seats
    • Custom data retention

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.
Dataiku review

Choose Traceloop if

  • You need open-source sdk (openllmetry).
  • You want to start without paying.
  • You work on Cloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby.
  • You also want multi-provider support.
Traceloop review

Questions people ask

Is Dataiku or Traceloop better?
Neither clearly leads. Dataiku starts at Free and Traceloop at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or Traceloop?
Dataiku starts at Free and Traceloop at Free.
Does Dataiku or Traceloop run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. Traceloop runs on Cloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby.
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 Traceloop is typically brought in for.
What can Dataiku do that Traceloop cannot?
Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. Traceloop covers Open-source SDK (OpenLLMetry), Multi-provider support, Observability platform integration, Framework 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.

Source
Traceloop: Is OpenLLMetry open-source?

Yes, OpenLLMetry is Traceloop's open-source SDK built on OpenTelemetry standards. It allows teams to instrument LLM applications with just 2 lines of code and send data to 25+ observability platforms.

Source
Dataiku: 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.

Source
Traceloop: What is the impact of ServiceNow acquisition?

Traceloop is joining ServiceNow, representing a strategic acquisition that will broaden enterprise adoption and integration capabilities. Current operations continue with free and enterprise options available.

Source
Traceloop: How many LLM providers and frameworks does Traceloop support?

Traceloop supports 20+ LLM providers including OpenAI and Anthropic, and integrates with frameworks like LangChain and LlamaIndex. It can send data to 25+ observability platforms.

Source
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