Workspaces
graal Data Platform offers three workspaces: Jupyter, VS Code and RStudio. They share the job scheduling mechanism: a workspace is a pod started in the execution namespace, under the same security constraints and the same project quota.
Jupyter
Section titled “Jupyter”The notebook a data science team asks for first. The image ships the libraries needed day to day: data manipulation, object storage access, a Trino client to query the warehouse, and an MLflow client to track experiments.
VS Code
Section titled “VS Code”code-server, for the data engineer who edits code rather than cells. Same base image, same
storage, same identity.
RStudio
Section titled “RStudio”RStudio Server, for teams that work in R. It opens from the console, behind the same gateway and the same authentication as Jupyter and VS Code.
A single door
Section titled “A single door”All three workspaces are served behind a single gateway. The practical consequence for your network team: one entry point to open, and one authentication — the console’s. No password per tool, no second directory.
The project’s data, without copying a credential
Section titled “The project’s data, without copying a credential”A workspace opens inside a project: it sees that project’s tables, buckets and secrets, with the rights of the person who opens it. A notebook that must run on its own becomes a job, schedulable and monitored like the others (see jobs and workflows).
Visualisation stays yours
Section titled “Visualisation stays yours”The Data Platform plugs into your dashboarding tool: Trino exposes a standard JDBC access that your BI tool queries directly.
Go further
Section titled “Go further”- Notebooks, the site page
- Runtime images
- Data and SQL
- Security and governance