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A powerful environment for Jupyter notebooks

Use smart coding assistance for Python in Jupyter notebooks, run code on powerful CPUs and GPUs, collaborate with your team in real time, and easily share the results.

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Speed up your Data Science work with Datalore

Start working in seconds with a pre-setup environment and intelligent code editor. Upload datasets to persistent storage, analyze data, and train machine learning models with powerful CPU and GPU machines. Share your work with a link and invite your team to collaborate.
Use code auto-completion and quick-fixes from PyCharm
Start quickly with pre-installed Python libraries
Generate automatic plots for DataFrames
Execute .py scripts and run sudo commands in Terminal
Learn from in-app documentation
Choose between pip and Conda package managers
Use code auto-completion and quick-fixes from PyCharm
Start quickly with pre-installed Python libraries
Generate automatic plots for DataFrames
Execute .py scripts and run sudo commands in Terminal
Learn from in-app documentation
Choose between pip and Conda package managers
Upload files and folders to persistent storage in the cloud
Create secret variables to store credentials
Mount S3 buckets inside notebooks
Navigate through notebooks using the table of contents
Upload files and folders to persistent storage in the cloud
Create secret variables to store credentials
Mount S3 buckets inside notebooks
Navigate through notebooks using the table of contents
Edit notebooks together in real time
Organize the team’s work in workspaces
Share datasets across the team using workspace files
Create history checkpoints and track changes
Edit notebooks together in real time
Organize the team’s work in workspaces
Share datasets across the team using workspace files
Create history checkpoints and track changes
Publish static copies of notebooks and share them by a link
Export notebooks to PDF, PY, HTML, IPYNB files
Describe data with Markdown and LaTex
Present results with interactive plots
Embed Datalore cells on social networks and other platforms
Publish static copies of notebooks and share them by a link
Export notebooks to PDF, PY, HTML, IPYNB files
Describe data with Markdown and LaTex
Present results with interactive plots
Embed Datalore cells on social networks and other platforms
Use powerful CPUs and GPUs
Switch on unlimited Background computations for long jobs
Share notebooks with edit access with an unlimited number of users
Run unlimited notebooks in parallel
Use powerful CPUs and GPUs
Switch on unlimited Background computations for long jobs
Share notebooks with edit access with an unlimited number of users
Run unlimited notebooks in parallel
Coding productivity
Working with data
Collaboration
Reporting
Pro features

Pricing

Community

Basic machines & limited features for beginner data scientists and analysts.
Free

Resources

  • 120 hours of computations on a basic CPU machine 
  • 10 hours of computations on a GPU machine* 
  • 10 GB of cloud storage + S3 bucket support 

Features

  • Keep machine running for 6 hours after you’re left notebook
  • Publishing and sharing of notebooks for unlimited viewers and up to 3 editors
  • 1 shared workspace
  • Run 2 notebooks in parallel
  • Version History

Professional

Powerful machines & unlimited features for advanced data scientists and analysts.
$19.90/month

Resources

  • Unlimited computation on a basic CPU machine 
  • 120 hours of computations on a powerful CPU machine 
  • 20 hours of computations on a GPU machine 
  • 20 GB of cloud storage + S3 bucket support 

Features

  • Keep machine running for unlimited time
  • Unlimited publishing and sharing of notebooks and workspaces
  • Unlimited notebooks in parallel
  • Version history
  • Membership in the Customer Advisory Board. Meet the Datalore team and impact product decisions

Enterprise

On-premises installation and dedicated support for companies and teams that require extra security and customization.
$125.00/month per user
Learn more
We offer several types of On-premises builds. Get more information here or contact sales for more information.
* One-time, after completing a short interview
Have more questions? Check out our documentation.