Machine Learning & Data Science · head to head
Jupyter vs Anaconda
Jupyter
Machine Learning & Data Science
Interactive computing across all programming languages
- From
- Free
- Rated
- -
Anaconda
Machine Learning & Data Science
The world's most popular data science platform
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Jupyter notebook format makes version control and collaboration difficult with multiple contributors; Anaconda dependency resolution slower than pip due to SAT solver complexity
- They diverge on capability: Jupyter covers Interactive notebooks, Anaconda covers Conda package manager.
Where they differ
Only the attributes on which Jupyter and Anaconda actually diverge.
Identical on both: starting price (Free), pricing model (Unknown), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).
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 Jupyter
- Interactive notebooks
- Live code execution
- Rich visualizations
- Markdown documentation
- Multi-language kernels
- Python
- R
- Julia
Only in Anaconda
- Conda package manager
- Environment management
- 1500+ packages
- Navigator GUI
- Cross-platform support
- Jupyter
- VS Code
- PyCharm
Both cover
- Linux support
- Mac support
- Windows support
What people use each for
The jobs each tool is most often brought in to do.
Jupyter
- Machine learning
- Data analysis
- Model training
- Predictive analytics
Anaconda
- Machine learning
- Data analysis
- Model training
- Predictive analytics
Both are used for machine learning, data analysis, model training, predictive analytics, on those jobs the choice comes down to price and fit rather than capability.
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Jupyter
- Notebook format makes version control and collaboration difficult with multiple contributors
- Performance degrades with large datasets due to loading entire dataset into memory
- Debugging capabilities limited compared to traditional IDEs
- No paid support or commercial backing
Anaconda
- Dependency resolution slower than pip due to SAT solver complexity
- Not all PyPI packages available through default Anaconda repository
- Requires paid licenses for organizations with 200+ employees
- Larger disk footprint than minimal Python installations
Pricing, plan by plan
Jupyter
FreeNo published plan breakdown. See the Jupyter review.
Anaconda
Free- FreeFree
- 600+ pre-installed packages
- Anaconda Navigator
- 5GB cloud storage
- Starter$15/month
- 10GB cloud storage per user
- Professional development environment
- Team workspace controls
- Business$50/month
- Automated vulnerability scanning
- Audit trails
- Enterprise SSO
Which should you pick?
Choose Jupyter if
- You need interactive notebooks.
- You want to start without paying.
- You work on Web, Cross-platform, Linux, macOS, Windows.
- You also want live code execution.
Choose Anaconda if
- You need conda package manager.
- You want to start without paying.
- You work on Windows, macOS, Linux, Web/Cloud.
- You also want environment management.
Questions people ask
- Is Jupyter or Anaconda better?
- Neither clearly leads. Jupyter starts at Free and Anaconda at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Jupyter or Anaconda?
- Jupyter starts at Free and Anaconda at Free.
- Does Jupyter or Anaconda run on more platforms?
- Jupyter runs on Web, Cross-platform, Linux, macOS, Windows. Anaconda runs on Windows, macOS, Linux, Web/Cloud.
- Can I use Jupyter for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Jupyter best used for?
- Jupyter is most often used for machine learning, data analysis, model training, predictive analytics.
- What can Jupyter do that Anaconda cannot?
- Jupyter covers Interactive notebooks, Live code execution, Rich visualizations, Markdown documentation. Anaconda covers Conda package manager, Environment management, 1500+ packages, Navigator GUI. Both handle Linux support, Mac support, Windows support.
Answered from the vendors’ own pages
Jupyter: Is Jupyter free to use?
Yes, Jupyter is completely free and open-source under the BSD license. There are no paid plans or commercial support requirements.
SourceAnaconda: Does Anaconda have a free version?
Yes. Anaconda Distribution is free and includes 600+ pre-installed data science packages, Navigator, and 5GB of cloud storage. Organizations with 200+ employees must use paid plans unless they qualify for academic or non-profit exemptions.
SourceJupyter: What programming languages does Jupyter support?
Jupyter supports Python plus over 40 additional programming languages including R, Julia, Scala, and many others through different kernels.
SourceAnaconda: What is the difference between Anaconda Distribution and Miniconda?
Anaconda Distribution includes 600+ pre-installed packages optimized for data science out of the box. Miniconda is lightweight with only conda, Python, and essential packages, requiring manual installation of additional libraries.
SourceJupyter: What is JupyterLab?
JupyterLab is the successor to classic Jupyter Notebook, adding a file browser, multiple tabs, terminal access, and an extension ecosystem for enhanced functionality.
SourceAnaconda: Does Anaconda integrate with VS Code?
Yes. Anaconda environments can be activated in VS Code, and you can run Jupyter Notebooks directly. Both JupyterLab and conda can be managed through the VS Code Jupyter extension.
SourceAnaconda: What platforms does Anaconda support?
Anaconda runs on Windows, macOS, and Linux, with cloud-based deployment options. Anaconda Notebooks provides a cloud-based JupyterLab environment requiring no local installation.
SourceAnaconda: Do all PyPI packages work with Anaconda?
Not all PyPI packages are available through Anaconda's default conda repository. When a package is unavailable in conda, you can install it from conda-forge or pip as an alternative.
Source