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Compare tools

Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

The New GitBook
✓ verifiedFreemium

Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.

👁 653K/mo2.9K
Open Source Database Designs
✓ verifiedFreemium

Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.

👁 27K/mo
Cody
✓ verifiedPaid

Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.

👁 245K/mo
Text2SQL
✓ verifiedPaid

AI tool that converts natural-language questions into SQL queries, sold via a Lemon Squeezy storefront with tiered pricing.

👁 20K/mo14K
Pricing

No public pricing

Free trial available

No public pricing

Enterprise: starting at $16K (includes AI feature credits, scales with team size)
Text2SQL.AI: $7.00-$48.00
Text2SQL.AI Pro: $29.00-$228.00

Free trial available

Core features
  • Publish structured documentation sites
  • Git sync for docs-as-code workflows
  • AI setup agent to build and import docs
  • GitBook MCP server for AI access
  • Enterprise controls
  • Free tier to start
  • Library of sample database designs
  • Visual database designer / diagram tool
  • AI database generator
  • Modify and optimize existing schemas
  • SQL script export
  • Dialect converters (MySQL/PostgreSQL/MSSQL)
  • Codebase-aware developer chat
  • AI code completions and inline edits
  • Customizable and shareable prompts
  • Automatic bug identification and debugging help
  • Context filters to exclude sensitive repos
  • Integrates with major code hosts and IDEs
  • Natural language to SQL query generation
  • Standard and Pro subscription tiers
  • Checkout and billing via Lemon Squeezy
Use cases
  • Publish product and API documentation
  • Maintain docs-as-code with Git sync
  • Make docs consumable by AI assistants
  • Import existing docs into a hosted site
  • Finding a starting schema for a project
  • Designing a database visually
  • Generating a schema with AI
  • Converting between SQL dialects
  • Engineers asking questions about an unfamiliar large codebase
  • Teams standardizing common coding tasks with shared prompts
  • Developers debugging errors faster with AI-assisted context
  • Enterprises running large-scale code migrations
  • Generating SQL queries without writing raw syntax
  • Helping non-technical users query databases
  • Speeding up ad hoc data lookups for analysts
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