Oracle Machine Learning Notebooks
Oracle Machine Learning Notebooks: A capable notebook environment for teams working inside Oracle Autonomous AI Database. Ranked #18 of 25 in Notebook Software by our editors (7.5/10); pricing: Paid; best for oracle-centered enterprise notebook workflows.
At a glance
- Editor score7.5 / 10
- PricingPaid
- Best forOracle-centered enterprise notebook workflows
- Free planNo
- Execution modelHosted
- Founded1977 · Austin, Texas, United States
- Facts checked20 Sep 2026
Where it wins
- Supports SQL, PL/SQL, Python, R, Markdown, and Conda interpreters
- Adds scheduling, version comparison, comments, and shared workspaces
- Supports GPUs, GitHub synchronization, and multiple notebook formats
Where it doesn't
- Requires Oracle Autonomous AI Database rather than operating standalone
- Web access is the only listed platform
- Paid access has no free plan
Our verdict on Oracle Machine Learning Notebooks
Oracle Machine Learning Notebooks is a hosted, web-based notebook environment for data scientists, data engineers, analysts, developers, and advanced SQL users. Its strongest fit is teams working with Oracle Autonomous AI Database, where notebooks can support data exploration, preparation, visualization, machine learning, and collaborative analysis. Shared workspaces, permissions, comments, and paragraph dependencies help teams organize work around common notebooks rather than isolated files.
Its integration model is central to the product. Oracle Machine Learning Notebooks connects with Oracle Autonomous AI Database and Oracle Object Storage, while GitHub import and synchronization support notebook workflows that include source control. Users can import and export native, Zeppelin, and Jupyter formats, including .dsnb, .json, and .ipynb. SQL, PL/SQL, Python, and R coverage gives the environment a broader language mix than a SQL-only workspace, and the Python interpreter supports GPU-backed execution for applicable workloads.
Operational features make it suitable for repeatable team workflows: notebook jobs can be scheduled, recurring jobs are supported, and built-in version history includes version comparison. The service is paid and does not offer a free plan, and it is accessed through Oracle’s cloud database platform rather than as a standalone desktop application. Choose it when Oracle database integration, collaboration, scheduling, and mixed-language analysis matter together. A different notebook product is likely a better fit for teams that need an independent desktop tool, a non-Oracle-centered environment, or a free starting plan.
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Oracle Machine Learning Notebooks pricing
Oracle Machine Learning Notebooks fact sheet
| Free plan | No |
|---|---|
| Paid from | Not verified |
| Execution model | Hosted |
| Real-time collaboration | Yes |
| Version history | Yes |
| GPU compute | Yes |
| Supported languages | SQL, PL/SQL, Python, R |
| Notebook formats | .dsnb, .json, .ipynb |
| Deployment | Cloud |
| Platforms | Web |
| Support | Docs |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Integrations | 3 integrations: GitHub, Oracle Autonomous AI Database, Oracle Object Storage |
| Pricing | Paid (source) |
| Website | docs.oracle.com |
| Facts checked | 20 Sep 2026 |
Oracle Machine Learning Notebooks integrations
Oracle Machine Learning Notebooks lists 3 integrations on its own site.
- GitHub
- Oracle Autonomous AI Database
- Oracle Object Storage
Alternatives to Oracle Machine Learning Notebooks
- 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 Oracle Machine Learning Notebooks alternatives →
Also Ranked In
Oracle Machine Learning Notebooks is ranked in 6 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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