Datalore
Datalore: A flexible notebook platform with collaboration, computation, reporting, and deployment options. Ranked #5 of 25 in Notebook Software by our editors (8.9/10); pricing: Free plan · 14-day trial; best for polyglot teams needing deployment options.
At a glance
- Editor score8.9 / 10
- PricingFree plan · 14-day trial
- Best forPolyglot teams needing deployment options
- Free planYes
- Execution modelHybrid
- Founded2000 · Amsterdam, Netherlands
- Facts checked20 Sep 2026
Where it wins
- Supports Python, SQL, R, Scala, and Kotlin notebooks
- Combines real-time collaboration, version history, and shared workspaces
- Offers cloud, API, and self-hosted deployment options
Where it doesn't
- Cloud Free excludes notebook version history
- GPU access is limited to paid Cloud computation and configurable On-Premises deployments
- The Cloud plan is listed without a separate plan price or distinct published entry
Our verdict on Datalore
Datalore is a collaborative data science notebook platform from JetBrains for teams working across analysis, reporting, and shared notebook workflows. It supports Python, SQL, R, Scala, and Kotlin, with database connections, SQL cells, CPU and GPU computation, interactive and static reports, scheduled runs, exports, and notebook execution through an API. Its deployment choices suit teams that want a hosted cloud service or organizations that require private infrastructure and custom environments.
The free Cloud Free plan includes unlimited notebooks, one shared workspace, one interactive shareable report, a Notebook API, and on-the-fly environment customization. The published paid Cloud starting price is 29.17 and adds Datalore AI, real-time collaboration, version history, unlimited database connections and SQL queries, and team management features. A 14-day free trial is available, although trial users cannot use Datalore credits. On-Premises supports a self-hosted or dedicated JetBrains-managed instance, unlimited free viewers, advanced team management, SSO options, and audit logs.
Datalore’s main strength is the combination of language breadth and workflow depth: teams can move from notebook execution to reports, scheduled runs, exports, and API-based execution without being limited to Python. Real-time collaboration and checkpoints support shared work, while CPU/GPU-backed computation expands the range of workloads it can accommodate. Teams should choose Datalore when they need multilingual notebooks, collaborative features, and a choice between hosted and private deployment. It is less suitable for teams that require version history on a free plan or GPU access without paid Cloud computation or a configurable On-Premises setup.
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Datalore pricing
All 3 Datalore plans and prices →
Datalore fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Not verified |
| Execution model | Hybrid |
| Real-time collaboration | Yes |
| Version history | Yes |
| GPU compute | Yes |
| Supported languages | Python, SQL, R, Scala, Kotlin |
| Notebook formats | .ipynb, .datalore, .zip, .py, .kts, .scala, .r, .html |
| Free trial | 14 days |
| Deployment | Cloud, Self-hosted |
| Platforms | Web |
| Compliance & security | SOC 2, GDPR, HIPAA |
| Support | Tickets, Community, Docs, Email |
| Built for | Solo, Small business, Mid-market, Enterprise (editorial estimate) |
| Pricing | Free plan · 14-day trial (source) |
| Website | jetbrains.com |
| Facts checked | 20 Sep 2026 |
Alternatives to Datalore
- Google ColabA capable browser notebook with free compute and paid access to more resources.9.4
- Jupyter NotebookA flexible, free notebook environment for code, narrative, visualizations, and data-science work.9.2
- JupyterLabA free, open-source notebook IDE with kernels, terminals, debugging, and extensions.9.1
See all Datalore alternatives →
Datalore vs the competition
- Datalore vs Google Colab
- Datalore vs Jupyter Notebook
- Datalore vs JupyterLab
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Also Ranked In
Datalore is ranked in 4 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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