This is the comparison we take most seriously. Directus got the big thing right years before we existed: the platform should sit on a SQL database you own, not replace it. Where we differ is the starting point — Directus is an admin studio for people who think in data models; SchemaStack is a spreadsheet that quietly builds the data model for you.
Directus is more mature and does more. This page is about whether you need what it does more of — or what we do differently.
Compared as of August 2026. Directus ships constantly — check their docs before making a decision on our say-so.
| Capability | SchemaStack | Directus |
|---|---|---|
Your data in your own Postgres or MySQL database | ||
Create and evolve real SQL schema from the UI Both can. Directus does it in its admin data-model settings; SchemaStack does it in the same spreadsheet your team works in. | ||
Migration dry run before a schema change Whether a migration is required, rows affected, locking behaviour, and the SQL — reported before anything is applied. | ||
Spreadsheet-first editor you can hand to non-technical teammates Directus's data studio is capable, but it reads as an admin console. Ours is built to feel like the spreadsheet your ops team already uses. | ||
Generated REST API with OpenAPI docs | ||
GraphQL API If your frontend team wants GraphQL, that's a point for Directus — we generate REST only. | ||
Connect Claude or ChatGPT with one URL — consent screen, scoped access, instant revocation Both ship an MCP server. The hosted-connector flow — self-registration, a consent screen naming app, workspace and permissions, and revocation that kills tokens already issued — is ours. | ||
AI access capped below schema changes An agent granted 'write' can edit records but never alter your schema; schema-level access requires a key an administrator creates deliberately. | ||
Guest links for a single view — time-limited, revocable, no account Directus can share individual items; a client-facing live table without provisioning users is a different thing. | ||
Built-in automation builder (flows) SchemaStack has webhooks; Directus Flows is a full visual automation system. If you'd replace Zapier with it, Directus wins here. | ||
Source-available and self-hostable Directus is BSL-licensed — free below a revenue threshold — and you can run it entirely inside your own network. We're hosted, full stop. | ||
Years of extensions, integrations and community answers Directus has been at this since 2004 in some form. We're in early access, and we won't pretend otherwise. |
In Directus, changing the data model is an administrator's task in a settings area. In SchemaStack, adding a column to the grid adds a real column; linking two tables creates a real foreign key or junction table. The person who understands the data shapes the database — without knowing they're doing DDL.
Every structural change is dry-run first: migration or not, how many rows, whether reads or writes will block, and the SQL that would run. On a production database, that's the difference between letting non-DBAs near the schema and forbidding it.
Paste one URL into Claude or ChatGPT. The agent registers itself, you approve it on a consent screen that names the app, the workspace and what it may do — and revoking it cuts off the tokens it's already holding, immediately. Directus has an MCP server; the governed connector journey is the part we built beyond that.
Directus can be your CMS, your automation engine, your dashboard layer and your API gateway. That breadth is real value — and real surface area. SchemaStack does one job: a governed, collaborative data layer on your database, for humans and agents. If you don't need the rest, you don't carry it.
Often, honestly. Directus is an excellent, battle-tested platform, and there are clear cases where it's the right answer:
Choose SchemaStack when the people shaping the data aren't database people, when you want schema changes previewed before they touch production, or when AI agents are part of who works in your data.
Start a 14-day Pro trial — no credit card. Connect your own Postgres or MySQL, or begin with a managed sample database and point it at your own later.
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