Datalore is JetBrains' collaborative, Jupyter-compatible data science notebook. See 2026 pricing, AI coding features, pros, cons and FAQs.
Category
Automation
Pricing
Freemium subscription with a free Cloud tier, a paid Cloud team tier, and custom On-Premises licensing, from Free Cloud plan available; paid Cloud plans and On-Premises pricing available on request
Verified
Not yet
Last updated
July 19, 2026
Founded
2018
Headquarters
Prague, Czech Republic (JetBrains headquarters)
Collaboration and AI Features in Datalore
Datalore notebooks support real-time, multi-user editing similar to a shared document, with notebooks shared by link or email invitation and either view or edit level access, and every notebook runs in its own isolated, managed environment.
Datalore AI assists with writing Python, SQL, and R code, generating explanatory text around findings, and fixing code errors, while the one-click interactive report feature turns a working notebook into a shareable, presentation-style document that hides code from the audience.
Cloud Free Plan versus Paid and On-Premises Options
The Cloud Free plan includes unlimited notebooks with collaboration, two parallel notebooks, one workspace, one interactive report, and 120 CPU-small machine hours with 10GB of storage, making it usable for individuals and students at no cost.
The paid Cloud plan adds Datalore AI, unlimited parallel notebooks, scheduled runs, and team management with a larger compute allowance, and pricing is provided on request; organizations needing to keep data on their own infrastructure can license the self-hosted On-Premises version instead.
Who Datalore Fits Best
Because Datalore is Jupyter-compatible, teams already working in Jupyter, JupyterLab, or Google Colab can generally import and export existing notebooks with minimal friction when adopting the platform.
It fits data science teams that want managed, governed collaboration without operating their own JupyterHub infrastructure, and organizations in regulated industries that need the On-Premises option to keep workloads inside their own security perimeter.
Key Features
Jupyter-compatible cloud notebooks — Notebooks remain compatible with the standard Jupyter format for easy import and export.
Real-time collaborative editing — Multiple users can co-edit the same notebook simultaneously with live cursors and changes.
Datalore AI coding assistant — Helps write Python, SQL, and R code faster, explain findings, and automatically fix code errors.
One-click interactive reports — Converts a working notebook into a shareable, presentation-style document that hides code cells.
Isolated notebook environments — Each notebook runs in its own environment with an integrated package and environment manager.
Scheduled notebook runs — Notebooks can be scheduled to run automatically on a recurring basis.