dbt Cloud Catalog
Great if you run dbt Cloud. Not available if you run dbt Core on premises. Taavik fills that gap with a tool that observes the actual database, not the dbt model.
Most database wikis are wrong within a week. Taavik fixes that by making the documentation a function of the schema. The agent scans, the diff updates the doc, the change history records when it happened. Manual notes stay where you wrote them.
What teams need from a database documentation tool
Confluence, Notion, dbDocs, ER diagrams in Lucidchart. They all share one problem: you have to remember to update them. After the third missed migration the team stops trusting the doc, and the doc dies.
A scan detects a new column. The doc shows it. A column gets dropped. The doc removes it and the change history records when. No manual sync.
The technical metadata is generated. The prose paragraphs are yours. Auto-updates touch the metadata only and never overwrite a description.
Every scan produces a diff. The doc shows the most recent changes per object, so a new hire reads the present and the recent past in one place.
An on-premise agent runs inside your network. The cloud receives metadata only. Compliance does not have to compromise.
Where Taavik fits
Great if you run dbt Cloud. Not available if you run dbt Core on premises. Taavik fills that gap with a tool that observes the actual database, not the dbt model.
Powerful, but require half a person to operate. Taavik is a single agent and a hosted control plane that keeps documentation alive without dedicated operators.
Static snapshots. Useful for a one-shot deliverable, painful as living documentation. Taavik refreshes on every scan and never asks you to re-run the export.
Easy to start, hard to keep current. Taavik moves the technical metadata to a tool that updates itself. Your wiki keeps the high-level prose; Taavik keeps the schema accurate.
What is supported
One workspace, many connections, many engines. Provider quirks normalized at scan time, the documentation reads consistently across databases.
Database engines
Generate PostgreSQL documentation from catalogs and keep schema changes visible.
Read provider pageDocument SQL Server metadata, notes, and change history from private scans.
Read provider pageKeep MySQL documentation current with metadata scans and preserved manual notes.
Read provider pageGuides
How generated metadata, manual notes, and schema changes become a documentation layer the team can trust.
Read the guideWhy private databases need an agent-based scan instead of direct cloud database access.
Read the guideA practical operating model for scans, change review, generated facts, and preserved manual notes.
Read the guideCompare
Compare broad data catalog workflows with focused private database documentation and operational SQL.
Read comparisonCompare visual design workflows with living documentation refreshed from database scans.
Read comparisonCompare DBML docs-as-code with scan-based documentation for private databases.
Read comparisonFAQ
PostgreSQL, MySQL, SQL Server, and Redshift. The on-premise agent connects to any of them and reads schema metadata through the standard information schema.
The control plane runs on EU-only infrastructure in Rimini, Italy. Only schema metadata and manual notes are stored. Row data never leaves your network.
The documentation is rendered in the workspace, served by the cloud control plane. The data behind it is catalog metadata, manual notes, and change history. Credentials stay local.
Yes. Add descriptions to tables, paragraphs to columns, known-issue blocks to objects. Auto-updates touch only the technical metadata; your text stays untouched.
Taavik documents the database as it is. dbt docs documents the dbt models you wrote. They serve different audiences. Many teams use both.
Free for one connection, forever. The agent is small. The first scan is fast.