Guide
Generate PostgreSQL schema documentation from catalogs and keep it updated after scans. Useful for teams with private PostgreSQL databases.
PostgreSQL schema documentation should explain the database that exists today, not the database that existed when someone last exported a diagram.
Postgres teams move quickly. Tables change during product work, indexes are added after performance reviews, views evolve for reporting, and foreign keys appear or disappear as the model matures. If documentation is maintained by hand, it usually loses the race.
Taavik generates database documentation from scanned metadata, tracks PostgreSQL schema changes, and supports an agent-based scan model for private databases.
Useful PostgreSQL documentation starts with catalog facts. The team should be able to open a table page and see the current technical shape without running a query.
At minimum, the documentation should include:
Those details are not editorial. They are generated from the database. Manual text should explain meaning, ownership, and caveats.
PostgreSQL already knows the schema. A documentation tool should use that fact.
Catalog-driven documentation avoids copy and paste work. It also reduces arguments about whether the wiki or the database is right. If the scan is current, the generated metadata reflects the database.
This does not remove the need for human context. It gives the human context a stable place to live. A developer can add a description to customer_status, while the system keeps the type, nullability, default, and change history current.
ER diagrams are useful for orientation, especially early in a project. They are less useful as the only documentation layer.
A one-time diagram usually misses operational details:
Diagrams also become difficult to review after frequent schema changes. The team needs a searchable object-level documentation surface, not only a picture.
Many PostgreSQL databases are not meant to accept connections from a hosted SaaS tool. They sit inside private networks, customer environments, or tightly controlled cloud accounts.
An agent-based scan respects that architecture. The agent runs where PostgreSQL is reachable, connects with the configured role, reads metadata, and sends the schema catalog to the documentation workspace.
For documentation, a restricted role is usually the right starting point. The role should have enough access to inspect metadata and no unnecessary write permissions.
The critical moment is after a migration.
A column rename can confuse a support workflow. A dropped index can explain a new performance problem. A new nullable column can signal an unfinished feature. If documentation is updated days later, the team loses that context.
Taavik compares scans and records schema changes next to the generated documentation. That makes the documentation useful during reviews, onboarding, and incident investigation.
Generated documentation should not try to guess business meaning. The team should write that part.
Useful manual notes include:
Keep notes short. The best database documentation is not a long essay. It is a current schema with clear context where the schema alone is not enough.
Start with the schemas and tables that create the most questions. For many SaaS products, that means accounts, users, subscriptions, invoices, jobs, audit logs, and integration tables.
Run the scan, review the generated table pages, and add manual descriptions only where a teammate would otherwise ask a question.
That approach creates value quickly. It also avoids the common trap of trying to document the entire database perfectly before anyone can use it.
Turn PostgreSQL metadata into living documentation.