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AI-powered IDE with code completion, generation, explanation and debugging, plus a cloud dev environment, for developers.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Browser-based AI dev workspace by Google for full-stack apps; being sunset on 22 Mar 2027, no new workspaces.
AI SQL query optimization tool for developers to detect performance bottlenecks and get explainable tuning recommendations.
No public pricing
No public pricing
No public pricing
No public pricing
Free trial available
- ✦AI code completion and snippet generation
- ✦Natural-language code generation
- ✦Code explanation and AI Q&A
- ✦Automated bug detection and fixes
- ✦Zero-config cloud development environment
- ✦Project creation from templates or Git
- ✦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)
- ✦Cloud workspaces for full-stack development
- ✦App Prototyping agent from natural language
- ✦Gemini AI for coding, debugging and docs
- ✦Repo import from GitHub, GitLab and Bitbucket
- ✦Web previews and Android emulators
- ✦Deploy to Firebase App Hosting, Hosting or Cloud Run
- ✦Zero-configuration SQL optimization across multiple database engines
- ✦AI-powered query rewriting engine
- ✦Bottleneck detection with smart index recommendations
- ✦Dual-pane SQL diff viewer for before/after comparison
- ✦AI query plan explainer with step-by-step reasoning
- ✦MyBatis XML auto-rewrite support
- →Writing and completing code faster with AI
- →Onboarding to unfamiliar codebases
- →Debugging and optimizing code
- →Spinning up dev environments in the browser
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Prototyping apps from a prompt or mockup
- →Building full-stack apps in the browser
- →Collaborating and sharing preview URLs
- →Deploying and monitoring apps quickly
- →Backend developers speeding up slow production queries
- →Teams reducing manual SQL tuning workload
- →Engineers wanting explainable reasoning behind optimization suggestions
- →Companies standardizing query performance across MySQL/PostgreSQL systems