Built to make warehouse schema delivery clear, collaborative, and fast
SchemaStruct started with a simple frustration: warehouse design work was split across SQL files, screenshots, docs, and review threads. We built one workflow for modeling, reviewing, and handing off schema changes without losing context.
Warehouse models deserve better tooling
They sit at the center of analytics delivery — and they deserve tooling that keeps review, implementation, and docs in sync.
Traditional schema tools break the review loop
Teams jump between SQL files, warehouse metadata, screenshots, and docs. That creates drift, slows approvals, and makes even simple warehouse changes harder than they need to be.
Model once, review cleanly, and hand off from the same source
SchemaStruct keeps the model editable as code and understandable as a diagram, so teams move from rough warehouse ideas to approved handoff artifacts without losing context.
The principles behind every workflow
These shape the editor, the AI workflows, and the way we think about collaboration.
Clarity over ceremony
Database design should feel readable and iterative. We focus on flows that make models easier to understand, review, and evolve.
Visual and textual, together
Schemas are easier to trust when diagrams and source stay in sync. We design every workflow around that shared source of truth.
Fast enough for thinking
From first draft to production export, the product keeps momentum high and friction low for technical teams.
How we think about product decisions
Model ideas before they become migrations.
Keep diagrams useful, not decorative.
Make collaboration feel native to schema work.
Treat AI as an accelerator, not a replacement for judgment.
Review warehouse changes before they become production work
Shape the model, route it through review, and hand off approved changes with cleaner SQL, dbt, and documentation.