Machine Learning · head to head
MLflow vs Stellarium
MLflow
Machine Learning
Open source platform for managing the ML lifecycle
- From
- Free
- Rated
- -
Stellarium
Education
Free open source desktop planetarium software, distinct from the paid Stellarium Mobile Plus app
- 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; Stellarium it is desktop-only software, so it has no native touch-optimised phone interface; the similarly named mobile app is a different paid product from a different company.
- They diverge on capability: MLflow covers Experiment tracking, Stellarium covers Photorealistic sky rendering.
- Prices and features above were last checked on 1 September 2026.
Where they differ
Only the attributes on which MLflow and Stellarium actually diverge.
| Attribute | MLflow | Stellarium |
|---|---|---|
| Pricing model | open-source | Open source, no licence fee |
| Platforms | Web, Python API, REST API | Windows, macOS, Linux |
| Category | Machine Learning | Education |
| 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 Stellarium
- Photorealistic sky rendering
- Large object catalogue
- Telescope control
- Scripting engine
- Free and open source
- Plugin ecosystem
What people use each for
The jobs each tool is most often brought in to do.
MLflow
- Machine learningnot Stellarium
- Data analysisnot Stellarium
- Model trainingnot Stellarium
- Predictive analyticsnot Stellarium
Stellarium
- A student or educator wanting a serious, scriptable planetarium tool without a budget line itemnot MLflow
- An amateur astronomer wanting telescope control from desktop software they can inspect and modifynot MLflow
- Someone running a planetarium display or public astronomy event on a scripted shownot MLflow
- A hobbyist who wants a large object catalogue without paying a subscription, and does not need a phone appnot 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
Stellarium
- It is desktop-only software, so it has no native touch-optimised phone interface; the similarly named mobile app is a different paid product from a different company.
- As a volunteer-maintained open source project, support is community-based rather than a guaranteed commercial help desk.
- The interface, while capable, is less immediately intuitive for a first-time user than a polished commercial phone app.
- Telescope control and some advanced plugins require additional setup that a non-technical user may find fiddly.
- Because it shares a name with the unrelated paid Stellarium Mobile Plus app, buyers researching pricing online can easily conflate the two products.
Pricing, plan by plan
MLflow
Free- Open SourceFree
- Experiment tracking
- Model registry
- Deployment tools
Stellarium
Free- Stellarium DesktopFree
- Full software, GPL licensed
- No account, ads or subscription
- Community-developed plugins
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 Stellarium if
- You need photorealistic sky rendering.
- You want to start without paying.
- You work on Windows, macOS, Linux.
- You also want large object catalogue.
Questions people ask
- Is MLflow or Stellarium better?
- Neither clearly leads. MLflow starts at Free and Stellarium at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, MLflow or Stellarium?
- MLflow starts at Free and Stellarium at Free.
- Does MLflow or Stellarium run on more platforms?
- MLflow runs on Web, Python API, REST API. Stellarium runs on Windows, macOS, Linux.
- 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 Stellarium is typically brought in for.
- What can MLflow do that Stellarium cannot?
- MLflow covers Experiment tracking, Model registry, Model packaging, Deployment. Stellarium covers Photorealistic sky rendering, Large object catalogue, Telescope control, Scripting engine.
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.
SourceStellarium: Is Stellarium really free?
The desktop software is free and open source under the GPL licence. The separate mobile app, Stellarium Mobile Plus, is a different paid product.
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.
SourceStellarium: Is the mobile app made by the same team?
No. Stellarium Mobile Plus is built by Noctua Software, a different company, and is sold on subscription.
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.
SourceStellarium: What platforms does the free version run on?
Windows, macOS and Linux desktop.
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
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