Object-level lineage is not enough. When a number in a dashboard is wrong, you need to know which raw column produced it — not just which table.
What Column Trace™ actually shows you
For every projected column in every view, CTE, or materialized table, SQLise maps the chain of source columns and transformations that produced it. Click a column on the right and the source columns light up on the left.
- Per-column edges, not just per-table edges.
- Transformations through CASE, COALESCE, SUM, window functions, and CTEs.
- Cross-database and cross-schema references resolved.
Example: a derived revenue column
v_daily_revenue.revenue traces back through v_order_revenue.order_total to order_items.quantity × order_items.unit_price. SQLise renders that path as a single connected sub-graph.
CREATE VIEW v_order_revenue AS
SELECT o.order_id,
SUM(i.quantity * i.unit_price) AS order_total
FROM orders o
JOIN order_items i ON i.order_id = o.order_id
GROUP BY o.order_id;Works on raw DDL — no warehouse access required
Paste your DDL or compiled dbt SQL. The parser builds the lineage graph locally without ever connecting to your data.
What it looks like
Frequently asked
Which SQL dialects support column-level lineage?
SQL Server, Snowflake, PostgreSQL, MySQL, and Oracle. The dialect is auto-detected from your DDL or you can pick it manually.
Does it follow column lineage through CTEs?
Yes. CTE columns are tracked as intermediate hops in the lineage graph and rendered in the column-level details panel.
Do I need to log in?
No. Paste SQL on the homepage and Column Trace™ renders immediately. Sign in only if you want to save projects or share results.