Workspace
Data grid & studios
Spreadsheet-style editing for SQL tables, MongoDB documents, and Redis keys.
The story
A ticket says invoice totals are wrong. Nina opens Data grid, filters Q2 rows, spots null foreign keys, clicks through to parents, edits inline — no CSV round trip, no psql UPDATE one-liner hunting.
The grid is spreadsheet familiarity with database guardrails: type-aware editors, FK navigation, bulk filters on wide tables. MongoDB documents and Redis keys get tailored studios instead of forcing relational columns where they do not belong.
Data grid is where data work actually happens — catalog tells you what exists; the grid lets you touch it.
Bridge path: /editor
Step 1
Filter wide tables, edit safely
Forty thousand rows become twelve after filters. Nina edits amount, tab to next cell, save — constraints surface before commit.
FK link jumps to clients row in one click.
Spreadsheet-style editing for SQL tables, MongoDB documents, and Redis keys. Bridge path /editor. Inline editing respects column types and NOT NULL. Bulk selection for export.
Step 2
MongoDB and Redis studios
On MongoDB Nina edits nested JSON; on Redis she inspects hash fields — same sidebar entry, engine-appropriate chrome.
No second Compass window for document fixes.
Document and key-value UIs adapt per engine. SQL grid remains default for relational engines.
Step 3
From grid to Query lab
Nina copies the filter as SQL, opens Query lab, runs EXPLAIN on the bulk fix, executes — audit trail in one app.
Support ticket closed before lunch.
Seamless handoff to Query lab. CSV export for postmortems. FK navigation pairs with Catalog → Foreign keys.
postgresql://, ssh://, sftp://, s3://, or smtp:// examples.Related connections