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Dbx → Xs Workbench

Dbx → Xs Workbench

dbx-workspace-explorer

|
2 installs
| (0) | Free
Browse Unity Catalog, jobs, pipelines, SQL warehouses and cost for any Databricks workspace — in a VS Code tab. No project or repo required.
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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Dbx → Xs Workbench

Browse Unity Catalog, jobs, pipelines, SQL warehouses, cost, governance and the audit log for any Databricks workspace, without leaving VS Code. No project, repo or framework required — it works in an empty folder.

Not affiliated with Databricks, Inc.

What you get

Twenty surfaces in one panel: Overview, Catalog, Search, Lineage, Notebooks, Workspace, Jobs, Pipelines, Runs, SQL editor, Warehouses, Clusters, Libraries, Published, Cost, Observability, Governance, Audit, Health, Settings.

Seven trees in the Activity Bar for the things you glance at while working elsewhere — the connection, the catalog, jobs, pipelines, recent runs, notebooks and warehouses. A job row runs; a warehouse row starts and stops.

Notebooks open as notebooks. A workspace notebook opens in VS Code's own notebook editor — real cells, real output, find-across-cells, the diff editor — rather than in a viewer that reimplements a worse one. Running a cell is off until you turn it on, because it spends the workspace's compute.

Workspace files open as files. A dbx: filesystem provider gives you the editor you already have: find, go-to-line, split view, diff. Read-only.

A SQL editor with drag-from-schema, real bind parameters, EXPLAIN without running, a query profile that names the two things that quietly ruin a query, and completion that resolves table aliases.

An assistant, on a serving endpoint in your own workspace — there is no key belonging to this product and no conversation leaves the workspace boundary. Reading is all it can do on its own; a change is proposed and runs only when you approve it. The same read-only tools are offered to this editor's own agent over MCP, registered for you rather than hand-configured.

Connecting

Five ways, and three of them never ask you to paste a secret here: a CLI profile from ~/.databrickscfg, browser OAuth through the Databricks CLI's own token cache, or an existing az login. A personal access token and a service principal are the other two.

Auth is handled by the Databricks SDK rather than reimplemented in TypeScript — unified auth is several thousand lines of security-sensitive code, and a second copy would be a worse one.

What it installs

The extension is about 700 KB. On first activation it provisions its own Python environment with uv — roughly 40 MB, a few seconds — and nothing else is downloaded. It ships no interpreter and no wheels, which is what keeps it three orders of magnitude smaller than bundling a runtime.

uv must be on PATH, or named in databricksExplorer.runtime.uvPath. For an internal package mirror, set databricksExplorer.runtime.indexUrl.

Requirements

VS Code 1.101 or later, and network access to your Databricks workspace.

Keyboard

⌘K / Ctrl-K command palette — searches page names, sections and keywords
⌘I / Ctrl-I the assistant dock
⌘B / Ctrl-B collapse the sidebar
⌘. / Ctrl-. focus mode: chrome away, content only
⌘⏎ / Ctrl-⏎ in the SQL editor, run the statement at the cursor
⌘⇧⏎ / Ctrl-⇧⏎ explain it instead of running it

Status

Early, and honest about it. Every surface listed above works against a real workspace. Not yet done: the optional local sandbox and offline AI tiers, and Marketplace publishing.

Building it, the conventions it follows, and the reasoning behind the parts that look unusual are all in the repository README.

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