Text2Query

Product Introduction

1. Text2Query is a browser-based tool that converts natural language questions into SQL and MongoDB queries using uploaded database schemas. It operates entirely client-side without requiring server processing or installations, ensuring data remains local to the user's device. The tool supports multiple database systems, including MySQL, PostgreSQL, and MongoDB, with plans to expand to Oracle and Firestore.
2. The core value lies in democratizing database query creation by eliminating the need for coding expertise, enabling users to interact with databases using plain English or Spanish. It automatically detects relationships within schemas and provides explanations for generated queries, making database interactions accessible to non-technical users and accelerating workflows for professionals.

Main Features

1. Users can upload SQL or MongoDB schema files in formats like SQL, TXT, or JSON, with support for files up to 200MB. The tool automatically parses table structures, columns, and relationships without requiring manual configuration.
2. The system automatically detects both explicit foreign key relationships and implicit connections between database entities. This enables accurate JOIN operations and nested document queries in MongoDB without manual schema annotation.
3. The interface accepts natural language questions in English or Spanish and generates corresponding database queries while providing step-by-step explanations. Users can modify and reuse queries within the same session through an interactive history feature.

Problems Solved

1. The product addresses the challenge of writing complex database queries without technical expertise, particularly for users unfamiliar with SQL syntax or MongoDB aggregation pipelines. It bridges the gap between natural language intent and precise database operations.
2. Target users include business analysts, data analysts, and non-technical stakeholders who need direct database access, as well as developers seeking to prototype queries faster. Educators teaching database concepts also benefit from the explanation feature.
3. Typical scenarios include generating reports from business data, extracting nested MongoDB documents, debugging existing queries, and training teams on database interaction patterns. It also aids in rapid prototyping during database design phases.

Unique Advantages

1. Unlike cloud-based alternatives, Text2Query runs fully in the browser with zero data transmission to external servers, offering unparalleled privacy for sensitive schemas. This contrasts with tools requiring API calls or cloud processing.
2. The tool innovates with dual-language support (English/Spanish) for query input and automatic relationship detection that works even with poorly documented schemas. Its upcoming multimodal interface will combine text and diagrams for query refinement.
3. Competitive advantages include simultaneous support for SQL and NoSQL systems, client-side execution, and session-based query editing. The planned integration with GPT-4 and Claude models will enhance query generation accuracy for complex scenarios.

Frequently Asked Questions (FAQ)

1. How does Text2Query ensure data privacy? Answer: All processing occurs client-side in the user's browser, with schemas never transmitted to external servers or stored after the session ends.
2. Which database systems are currently supported? Answer: The tool supports MySQL, MariaDB, PostgreSQL, SQLite, SQL Server, and MongoDB, with Oracle and Firestore support planned for future updates.
3. What are the file size limitations for schema uploads? Answer: Users can upload schema files up to 200MB in SQL, TXT, or JSON formats, covering most standard database structures.