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Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Local desktop app that assembles code-context prompts for LLMs, with API integrations, token tracking, and prompt saving.
AI tool that explains, optimizes, refactors and reviews code, with playful explanation styles for learners.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦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)
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Source-code context and prompt management
- ✦Custom and formatting instructions
- ✦BYOK API integrations (OpenAI, Claude, Gemini, etc.)
- ✦Token-limit tracking
- ✦Code-edit feature with visual diffs and backups
- ✦Local, offline prompt generation
- ✦AI code explanation in plain language
- ✦Multiple explanation styles/personas
- ✦Code optimization suggestions
- ✦Code refactoring
- ✦Code review
- ✦Example algorithms to learn from
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Building context-rich prompts for AI coding
- →Comparing model outputs on the same task
- →Reusing saved prompts across tech stacks
- →Keeping code private during prompt creation
- →Understanding unfamiliar code
- →Learning how algorithms work
- →Refactoring and cleaning up code
- →Getting a quick AI code review
- →Explaining code to beginners