Use Case: Snowflake

SQL Data Lineage for Snowflake

Visualize Snowflake DDL, views, streams, tasks, pipes, and stages — with column-level lineage, no warehouse credits required.

Snowflake's ACCOUNT_USAGE only gives you object dependencies. Column-level lineage and pipeline-aware lineage (stages, streams, tasks) are not in the box.

Snowflake-aware parsing

STAGE, STREAM, PIPE, TASK, MATERIALIZED VIEW, and SEQUENCE are all first-class node types. The graph spans your full ingest pipeline, not just the SELECTs.

VARIANT-friendly column lineage

When you cast raw:order_id::NUMBER, the lineage tracks the path from the source VARIANT column all the way into the warehouse table.

Works without a warehouse connection

Run SHOW objects + GET_DDL once, paste the output, and explore. Or pipe the output of a small script. Nothing leaves your laptop unless you choose Query Lens™.

What it looks like

Snowflake stage → table → stream → task → mart.

Snowflake users typically need Architect (2,000 objects per parse) or Enterprise (30,000) for full-account lineage runs.

Frequently asked

Do you support MATERIALIZED VIEW?

Yes — materialized views are tracked like views with their own dependency edges and column lineage.

What about COPY INTO @stage?

COPY INTO data flows through stages are represented as edges between the source object and the stage.

Visualize your Snowflake DDL

Paste GET_DDL output and go.

Snowflake Pipeline Example Trace Column Lineage in Snowflake Column Trace™