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Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
AI tool that converts natural-language questions into SQL queries, sold via a Lemon Squeezy storefront with tiered pricing.
AI SQL toolkit for analysts and developers to generate, optimize, validate, format and explain queries across 30+ database engines.
Free trial available
No public pricing
Free trial available
Free trial available
- ✦150+ recommendations across 50+ AWS services
- ✦Zombie and unused resource cleanup
- ✦Over-provisioned rightsizing
- ✦Idle-resource scheduler
- ✦SpotBot for ECS Fargate spot/on-demand switching
- ✦AWS console extension with Slack/Teams alerts
- ✦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)
- ✦Natural language to SQL conversion
- ✦Database schema integration for accurate queries
- ✦Supports PostgreSQL, MySQL, Oracle, SQL Server and more
- ✦Insights with queries, results, visualizations and explanations
- ✦Desktop app for local database connections
- ✦Public API for custom integrations
- ✦Natural-language to SQL/NoSQL query generation
- ✦AI-driven query optimization with rewrite suggestions
- ✦Syntax validation with automated error fixes
- ✦Query formatting and cross-engine conversion
- ✦Schema-aware data source connections with autosuggest
- ✦Rule-based guardrails per connected data source
- ✦Support for large schemas with 900+ tables
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Generating SQL queries without writing raw syntax
- →Helping non-technical users query databases
- →Speeding up ad hoc data lookups for analysts
- →Analysts writing SQL without deep query-syntax knowledge
- →Developers debugging and optimizing slow queries
- →Teams standardizing SQL formatting across a codebase
- →Migrating queries between database engines
- →Learners wanting plain-language explanations of SQL statements