dbdocs vs tbls

dbdocs creates web-based database documentation from DBML definitions. DBML is an open-source markup language for defining database structures; published documentation lets readers browse tables and fields and view relationships between tables. Teams can store DBML locally or in Git, then publish it to a dbdocs project. The db2dbml command supports imports from PostgreSQL, MySQL, MSSQL, Snowflake, and BigQuery. Documentation views can be embedded in Notion, Confluence, Miro, or a website. CI publishing uses a token, and the instructions include a GitHub Actions example. New projects are public by default. The Free plan lists password-protected sharing, while private mode is available on paid plans. The cloud service includes schema history and a data dictionary, and its stated database coverage is relational. dbdocs is aimed at internal development teams and software development agencies. The Free plan is free. Personal Pro costs $20 a month, or $16/month annually; Team costs $60 a month, or $50/month annually.

tbls is a command-line tool for documenting databases and checking their schemas. It generates GitHub Flavored Markdown and can export schema information in formats including DOT, PlantUML, Mermaid, SVG, PNG, JPG, JSON, YAML, Excel, and configuration files. Its configurable lint rules can require column comments or set column-count limits. The `diff` command compares a database schema with generated documentation or another database, while `coverage` measures documentation for descriptions and comments. Documented data sources include PostgreSQL, MySQL, MariaDB, SQLite, BigQuery, Cloud Spanner, Amazon Redshift, SQL Server, Azure SQL, Microsoft Fabric Warehouse, DynamoDB, Snowflake, MongoDB, ClickHouse, Databricks, JSON, HTTP, and GitHub. Docker and a GitHub Action are documented for CI use, and external drivers can extend database support. It runs on Linux, macOS, and Windows, or in a self-hosted setup. The listed plan is free under the MIT License. SQL Server requires version 2017 or later and database compatibility level 110 or higher.