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Taavik vs tbls

Taavik

taavik.com

tbls

github.com

Side by side

FigureTaaviktbls
Price from€39/moFree
Free planYesYes
Free trial——
Open source——
WebYes—
WindowsYesYes
macOS—Yes
LinuxYesYes
APIYes—
Self-hostedYesYes
Plans published31
Spec score · Database Documentation Tools8.0 (#13)8.2 (#9)
Supported databasesTaavik supports PostgreSQL, SQL Server, MySQL, and Amazon Redshift.Documented data sources include PostgreSQL, MySQL, MariaDB, SQLite, BigQuery, Cloud Spanner, Redshift, SQL Server, DynamoDB, Snowflake, MongoDB, ClickHouse and Databricks.

Plans

Taavik

  • FreeFree
  • Pro€39 a month
  • EnterprisePriced on request

Taavik pricing →

tbls

  • Open-source softwareFree

tbls pricing →

In their own words

Taavik

Taavik generates database documentation from schema scans, keeps it updated as schemas change, and preserves manual notes. It supports PostgreSQL, SQL Server, MySQL, and Amazon Redshift. Each scan creates a schema difference, while object pages show recent changes. Teams can save and share read-only SQL queries with typed variables, version history, and execution audit records. Scheduled queries can export CSV or Excel results to Slack or email. A read-only MCP connector exposes scanned schema to compatible clients including Claude Code, Cursor, and Windsurf. Taavik uses hybrid deployment: its cloud control plane runs on dedicated virtual machines in the European Union, while database rows remain in the customer network except during queries or schedules. The on-premise agent runs on Windows, Linux, or Docker. The Free plan costs nothing and covers one database server, two members, and 30 days of history.

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tbls

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.

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