Explore tables and columns before you write SQL
Different databases usually mean different tools. Here you list connections, inspect tables and columns, and refresh metadata after upstream changes. The workflow stays the same whether you're on Postgres, Snowflake, or something else.
How it works
Step 1: Pick the connection
What data sources are connected in this workspace, and what short name should I use for each when I run commands?Step 2: Inspect tables and columns
On our finance database, list tables whose names start with “revenue.” For each one I need every column: its name, type, and whether blank values are allowed.Step 3: After the database schema changes
Finance changed their database structure. Refresh my catalog here so what I see matches what’s actually there now.connections refresh reconciles the catalog in the background. Let it settle before tables list reflects brand-new DDL.
Step 4: Page through a wide catalog
Give me a browseable snapshot: up to 50 tables from finance with full column details so I can skim what exists.Who uses this
- Anyone writing SQL or filters who wants names and types confirmed first.
- Engineers building table pickers on top of workspace catalog output.
- Teams checking renames before dashboards ship.
- Agent tooling that should only touch columns the catalog actually lists.