Software · head to head
Baserow vs scikit-learn
The short version
- Each has a real cost: Baserow the free tier is capped at 3,000 rows and 2GB of storage per workspace; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays
- They diverge on capability: Baserow covers Database tables, scikit-learn covers Classification algorithms.
Where they differ
Only the attributes on which Baserow and scikit-learn actually diverge.
| Attribute | Baserow | scikit-learn |
|---|---|---|
| Pricing model | freemium | Unknown |
| Platforms | Web, Api, Self-hosted | Python, Linux, macOS, Windows |
| Founded | 2019 | 2007 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 Baserow
- Database tables
- Multiple views
- Forms
- API access
- Real-time collaboration
- Templates
- Plugins
- Self-hosting
Only in scikit-learn
- Classification algorithms
- Regression models
- Clustering methods
- Dimensionality reduction
- Model selection
- NumPy
- SciPy
- Pandas
What people use each for
The jobs each tool is most often brought in to do.
Baserow
- Self-hosting an open source alternative to a spreadsheet databasenot scikit-learn
- Structured team data with Kanban, calendar and grid viewsnot scikit-learn
- Building internal tools on top of a database with an APInot scikit-learn
- Sharing data with external app users without giving them full seatsnot scikit-learn
scikit-learn
- Machine learningnot Baserow
- Data analysisnot Baserow
- Model trainingnot Baserow
- Predictive analyticsnot Baserow
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Baserow
- The free tier is capped at 3,000 rows and 2GB of storage per workspace
- Kanban, calendar and survey views need Premium at $10 per user per month billed yearly
- Role-based permissions, audit logs and SSO require Premium or higher
- Row limits are per workspace rather than per table, so splitting data across bases does not raise the ceiling
- Automation runs are metered as credits, 2,000 a month on free
scikit-learn
- No GPU acceleration by default; limited optional GPU support requires external arrays
- Single-machine only; no built-in distributed computing across clusters
- All datasets must fit entirely in RAM; no out-of-core learning
- No production-grade deep learning; neural network support limited to basic multilayer perceptron
- No reinforcement learning algorithms
Pricing, plan by plan
Baserow
Free- FreeFree
- Unlimited rows
- Core features
- Community support
- Premium$5/user/month
- Row comments
- Kanban view
- Survey form
scikit-learn
FreeNo published plan breakdown. See the scikit-learn review.
Which should you pick?
Choose Baserow if
- You need database tables.
- You want to start without paying.
- You work on Web, Api, Self-hosted.
- You also want multiple views.
Choose scikit-learn if
- You need classification algorithms.
- You want to start without paying.
- You work on Python, Linux, macOS, Windows.
- You also want regression models.
Questions people ask
- Is Baserow or scikit-learn better?
- Neither clearly leads. Baserow starts at Free and scikit-learn at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Baserow or scikit-learn?
- Baserow starts at Free and scikit-learn at Free.
- Does Baserow or scikit-learn run on more platforms?
- Baserow runs on Web, Api, Self-hosted. scikit-learn runs on Python, Linux, macOS, Windows.
- Can I use Baserow for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Baserow best used for?
- Baserow is most often used for self-hosting an open source alternative to a spreadsheet database, structured team data with kanban, calendar and grid views, building internal tools on top of a database with an api, sharing data with external app users without giving them full seats. Of those, self-hosting an open source alternative to a spreadsheet database and structured team data with kanban, calendar and grid views are not what scikit-learn is typically brought in for.
- What can Baserow do that scikit-learn cannot?
- Baserow covers Database tables, Multiple views, Forms, API access. scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction.
Answered from the vendors’ own pages
scikit-learn: Does scikit-learn support GPU acceleration?
Scikit-learn has no native GPU support by design to keep installation simple and cross-platform. Since 2023, a limited number of estimators can run on GPUs if input data is provided as PyTorch or CuPy arrays, but this requires additional setup.
Sourcescikit-learn: Can scikit-learn handle datasets larger than RAM?
No. Scikit-learn is built on NumPy which requires all data to fit in memory, and NumPy operates on single-machine CPUs only. For very large datasets, consider Spark MLlib or distributed alternatives.
Sourcescikit-learn: Is scikit-learn free to use commercially?
Yes. Scikit-learn is open source under the BSD license, which allows free commercial use, modification, and distribution.
Sourcescikit-learn: What neural network capabilities does scikit-learn have?
Scikit-learn includes only a basic multilayer perceptron (MLPClassifier and MLPRegressor) for simple feedforward networks. For serious deep learning, use PyTorch, TensorFlow, or Keras instead.
Sourcescikit-learn: Does scikit-learn include natural language processing?
Scikit-learn has minimal NLP support limited to basic text feature extraction and vectorization. For comprehensive text processing, use spaCy or NLTK instead.
Sourcescikit-learn: When was scikit-learn first released?
Scikit-learn's first public release was February 1, 2010, following its start as a Google Summer of Code project in 2007.
SourceRelated pages
More on scikit-learn
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