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Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Open-source SDK and viewer for logging, querying, and visualizing multimodal robotics data, with a paid managed Hub for scale.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
AI SQL toolkit for analysts and developers to generate, optimize, validate, format and explain queries across 30+ database engines.
No public pricing
No public pricing
Free trial available
- ✦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)
- ✦Open-source Python, Rust, and C++ logging SDK
- ✦Interactive desktop and web viewer for reviewing recordings
- ✦SQL and dataframe queries across logged data
- ✦Column-chunk .rrd storage format for multimodal data
- ✦PyTorch dataloader for training directly on recordings
- ✦Commercial Hub with managed catalog, SSO, and byte-range indexing
- ✦Used in robotics projects like LeRobot, Brush, and PyCuVSLAM
- ✦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
- ✦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
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Robotics teams debugging calibration and training runs
- →Visualizing and querying large multimodal sensor datasets
- →Streaming training data mixes directly to GPUs at scale
- →Sharing annotated recordings across a robotics engineering team
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →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