Machine Learning · head to head
MLflow vs Ory Kratos
MLflow
Machine Learning
Open source platform for managing the ML lifecycle
- From
- Free
- Rated
- -
The short version
- Each has a real cost: MLflow requires infrastructure setup: teams must manage MLflow tracking server, database, and artifact storage themselves; Ory Kratos headless means you build every screen, which is significant work compared with a hosted login page
- They diverge on capability: MLflow covers Experiment tracking, Ory Kratos covers Headless API.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which MLflow and Ory Kratos actually diverge.
| Attribute | MLflow | Ory Kratos |
|---|---|---|
| Pricing model | open-source | Open-source self-hosted, with a paid managed network |
| Platforms | Web, Python API, REST API | Linux, Docker, Kubernetes, Self-hosted |
| Category | Machine Learning | Cybersecurity |
| Founded | 2018 | Unknown |
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 MLflow
- Experiment tracking
- Model registry
- Model packaging
- Deployment
- Project organization
- TensorFlow
- PyTorch
- scikit-learn
Only in Ory Kratos
- Headless API
- Self-service flows
- Multi-factor authentication
- Pluggable identity schemas
What people use each for
The jobs each tool is most often brought in to do.
MLflow
- Machine learningnot Ory Kratos
- Data analysisnot Ory Kratos
- Model trainingnot Ory Kratos
- Predictive analyticsnot Ory Kratos
Ory Kratos
- Products needing complete control over the look and flow of authenticationnot MLflow
- Applications that must not hand user identity data to a third partynot MLflow
- Teams building identity as infrastructure across several servicesnot MLflow
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
MLflow
- Requires infrastructure setup: teams must manage MLflow tracking server, database, and artifact storage themselves
- Basic UI and visualization: lacks rich interactive dashboards and real-time monitoring compared to commercial platforms
- Limited collaboration: no built-in role-based access control or multi-user management features
- Production monitoring gaps: drift detection, explainability, and alerting require separate dedicated tools
Ory Kratos
- Headless means you build every screen, which is significant work compared with a hosted login page
- More moving parts than a monolithic IAM: Kratos handles identity, and OAuth2 needs Ory Hydra alongside
- Documentation assumes real familiarity with identity concepts and is not a gentle introduction
- Self-hosting identity carries the security and availability burden that hosted providers absorb
Pricing, plan by plan
MLflow
Free- Open SourceFree
- Experiment tracking
- Model registry
- Deployment tools
Ory Kratos
Free- Self-hostedFree
- Full identity server
- All flows
- Community support
Which should you pick?
Choose MLflow if
- You need experiment tracking.
- You want to start without paying.
- You work on Web, Python API, REST API.
- You also want model registry.
Choose Ory Kratos if
- You need headless api.
- You want to start without paying.
- You work on Linux, Docker, Kubernetes, Self-hosted.
- You also want self-service flows.
Questions people ask
- Is MLflow or Ory Kratos better?
- Neither clearly leads. MLflow starts at Free and Ory Kratos at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, MLflow or Ory Kratos?
- MLflow starts at Free and Ory Kratos at Free.
- Does MLflow or Ory Kratos run on more platforms?
- MLflow runs on Web, Python API, REST API. Ory Kratos runs on Linux, Docker, Kubernetes, Self-hosted.
- Can I use MLflow for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is MLflow best used for?
- MLflow is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Ory Kratos is typically brought in for.
- What can MLflow do that Ory Kratos cannot?
- MLflow covers Experiment tracking, Model registry, Model packaging, Deployment. Ory Kratos covers Headless API, Self-service flows, Multi-factor authentication, Pluggable identity schemas.
Answered from the vendors’ own pages
MLflow: Is MLflow free to use?
Yes, MLflow is completely open-source and free. However, teams typically incur infrastructure costs for hosting and maintaining the MLflow tracking server. Databricks offers Managed MLflow as a commercial option for cloud deployment.
SourceOry Kratos: Is Ory Kratos free?
Yes, open source and free to self-host. Ory Network is a paid managed service.
MLflow: Can MLflow track experiments for different ML frameworks?
Yes, MLflow is framework-agnostic and works with TensorFlow, PyTorch, scikit-learn, XGBoost, and any other ML framework. This flexibility is a core design principle allowing teams to use diverse tools.
SourceOry Kratos: What does headless mean here?
Kratos provides identity flows as APIs and no user interface. You build the login, registration and recovery screens yourself.
MLflow: Does MLflow include a model registry?
Yes, MLflow Model Registry (added in 2018) provides a central model store with versioning, stage transitions, and deployment tracking. This enables production model governance and lineage tracking.
SourceOry Kratos: Does Kratos do OAuth2?
No. Kratos handles user identity; OAuth2 and OpenID Connect provider functionality is Ory Hydra, a separate component.
MLflow: What are MLflow's main limitations?
MLflow requires significant infrastructure setup and maintenance. The UI is basic compared to commercial tools, collaboration is limited without third-party RBAC solutions, and production monitoring requires separate tools for drift detection and alerting.
SourceMLflow: Can MLflow handle LLM and agent tracing?
MLflow added LLM and agent tracing capabilities in recent versions, though the native support is limited compared to specialized LLM observability platforms that replaced weak LLM tracing.
SourceRelated pages
Other head to heads
- MLflow vs Comet ML
- MLflow vs Weights & Biases
- MLflow vs Neptune.ai
- MLflow vs ClearML
- MLflow vs DVC
- MLflow vs Kubeflow
- MLflow vs BentoML
- MLflow vs AWS SageMaker
- MLflow vs DataRobot
- MLflow vs Seldon
- MLflow vs Azure Machine Learning
- MLflow vs Dataiku
- MLflow vs Palantir Foundry
- MLflow vs Pinecone
- MLflow vs Python
- MLflow vs PyTorch
- MLflow vs scikit-learn
- MLflow vs Apache Spark MLlib
- MLflow vs Logto
- MLflow vs Authelia
- MLflow vs 1Password
- MLflow vs authentik
- MLflow vs Clerk
- MLflow vs Trivy
- MLflow vs LastPass
- MLflow vs HashiCorp Vault
- MLflow vs Bitwarden
- MLflow vs Frontegg
- MLflow vs Infisical
- MLflow vs Semgrep
- MLflow vs Envysion
- MLflow vs Feedzai
- MLflow vs HashiCorp Boundary
- MLflow vs JumpCloud
- Ory Kratos vs Comet ML
- Ory Kratos vs Weights & Biases
- Ory Kratos vs Neptune.ai
- Ory Kratos vs ClearML
- Ory Kratos vs DVC
- Ory Kratos vs Kubeflow
- Ory Kratos vs BentoML
- Ory Kratos vs AWS SageMaker
- Ory Kratos vs DataRobot
- Ory Kratos vs Seldon
- Ory Kratos vs Azure Machine Learning
- Ory Kratos vs Dataiku
- Ory Kratos vs Palantir Foundry
- Ory Kratos vs Pinecone
- Ory Kratos vs Python
- Ory Kratos vs PyTorch
- Ory Kratos vs scikit-learn
- Ory Kratos vs Apache Spark MLlib
- Ory Kratos vs Logto
- Ory Kratos vs Authelia
- Ory Kratos vs 1Password
- Ory Kratos vs authentik
- Ory Kratos vs Clerk
- Ory Kratos vs Trivy
- Ory Kratos vs LastPass
- Ory Kratos vs HashiCorp Vault
- Ory Kratos vs Bitwarden
- Ory Kratos vs Frontegg
- Ory Kratos vs Infisical
- Ory Kratos vs Semgrep
- Ory Kratos vs Envysion
- Ory Kratos vs Feedzai
- Ory Kratos vs HashiCorp Boundary
- Ory Kratos vs JumpCloud