DataDocs vs LLMSchema

DataDocs is a cloud database documentation tool that uses AI to generate documentation and keep it aligned with schema changes. It currently supports PostgreSQL and MySQL; SQL Server and Snowflake are listed as coming soon. One-click generation creates documentation, while search covers the documentation and data catalog. DataDocs scans for schema changes and reflects them in the documentation. If an asset’s documentation is wrong, users can regenerate it and provide feedback; manual editing is listed as planned. The service requests read-only metadata access and says it does not access or store the database’s actual data. Its web application and extraction service run in separate VPCs, with credentials stored in a restricted vault. DataDocs is aimed at small businesses, freelancers, and agencies, and is positioned as documentation software rather than data governance. The Free plan is free for one source, 25 assets, and weekly refresh. Growth costs $25 a month; Premium costs $100 a month.

LLMSchema is free, MIT-licensed software that generates database schema documentation for LLMs and AI agents. It extracts relational schemas from PostgreSQL, MySQL, and SQLite, then documents tables, columns, types, indexes, constraints, and relationships in Markdown. The default output is one portable Markdown document. An alternate layout creates an overview plus a separate Markdown file for each table. Users can include selected tables or exclude tables from the generated documentation. LLMSchema is available as a command-line tool and a Go library, with installation instructions for Go and a quick install script for macOS and Linux. The README shows adding schema generation to a Makefile or migration script to keep documentation current. It also suggests pointing a coding agent to the schema files from AGENTS.md, CLAUDE.md, or an equivalent instruction file. The project is self-hosted and listed for Linux, macOS, and Windows. Its maker positions it for development databases and says not to rely on it for production-critical documentation.