Text2Query: a tool for generating SQL and MongoDB query statements using natural language

Text2Query is a tool that uses artificial intelligence technology to convert natural language (e.g., everyday questions) into query statements that can be executed directly in a database. Users don't need to learn complex SQL or MongoDB syntax, they just need to ask a question in simple English or Spanish and the tool will automatically generate the corresponding query code. One of the main features of this tool is its focus on user privacy, as it runs entirely in the user's browser and the database structure information uploaded by the user is not stored on an external server. It supports users to upload their own database structure files (schema), so that AI can generate more precise and optimized query statements based on specific database tables and fields. For developers, product managers or data analysts, this is a tool that can significantly improve the efficiency of data queries.

Function List

• Natural Language to Query Statements: Support for converting everyday questions in English or Spanish into SQL or MongoDB query statements.
• Support for multiple databases: Queries can be generated for both major databases, SQL and MongoDB.
• Upload database structure: Users can upload the structure (schema) of their database, allowing AI to generate more accurate queries based on specific table and field names.
• Running within the browser: All operations are done locally in the user's browser without uploading user data to the server, protecting data privacy.
• No coding required: Users don't need to write any code to interact directly with the database and get data.
• free of charge: The tool is currently offered as a free service.

Using Help

Text2Query provides a very intuitive and simple interface that makes it easy for users unfamiliar with database syntax to retrieve data from databases. At its core, it utilizes AI to translate natural language questions such as "How many users signed up last month?" into SQL or MongoDB query commands that a computer can understand.

workflow

The whole process of using it is very simple and can be divided into the following steps:

1. Select database type:
   Once you are on the site, you will first need to select your database type.Text2Query currently supports two main types:SQL cap (a poem) MongoDB. You can find a toggle option on the page to choose according to your needs.
2. Upload database structure (Schema):
   In order for AI to understand what kind of tables and fields are in your database, you need to provide information about the structure of your database. By clicking the "Upload Schema" or similar button, you can upload a file containing the database structure.
   • with regards to SQL database, which is usually a .sql file, which contains the table that creates the table (CREATE TABLE) statements.
   • with regards to MongoDB, you need to provide a data structure that describes the JSON Documentation.
     Uploading the structure file is a critical step because AI generates query statements based on the table names, field names, and relationships between them that you provide. An accurate structure file can greatly improve the accuracy of the generated queries.
3. Enter your question:
   In the text input box on the page, enter the question you want to inquire about in your natural language (currently English or Spanish is supported). You can ask questions directly as if you were having a conversation with a human being.
   • For example, you could type, "Show me all users from California who signed up last week.".
   • Or for sales data, you could ask, "What were the total sales for each product category in the last month?" (query the total sales for each product category in the last month).
4. Generate and view queries:
   After entering your question, click "Generate Query" or a similar button, and the AI will immediately begin to analyze your question and database structure, and generate the corresponding query statement below.
   • generated SQL statements will be clearly displayed, for example SELECT * FROM users WHERE state = 'California' AND signup_date >= 'YYYY-MM-DD';The
   • You can copy the generated code here and paste it into your database management tool (e.g. MySQL Workbench, DBeaver, etc.) for execution.

Featured Functions

• Privacy: One of the greatest features of Text2Query is its privacy-preserving mechanism. All calculations, including the analysis of the database structure and the generation of query statements, are done locally in your browser. This means that none of your sensitive data will ever leave your computer, perfect for working with in-house or databases containing private information.
• Instant Feedback: The tool is very responsive, and the generated query statement and corresponding explanation can be seen almost immediately after entering a question. This greatly facilitates rapid data exploration and analysis, allowing users to quickly iterate through their questions until they find the data they need.
• No registration required: No account or login is required to use the site; you can start using it by opening the web page directly, further simplifying the process.

With a few simple steps like this, users of any background, whether they are technical developers or non-technical business people, can quickly and securely get the information they need from the database without spending a lot of time learning and writing complex query statements.

application scenario

1. Rapid data analysis
   For product managers or marketing analysts who often need to quickly extract data from databases to support decision making, but may not be familiar with SQL, they can use Text2Query to ask questions directly in natural language, such as "Count the number of user growth per channel in the last quarter", to quickly get the data they need for reporting without having to wait for developer support. data quickly without waiting for developer support.
2. Assisted Development and Learning
   For beginner developers or students who are learning about databases, this tool can be a great aid. When they are not sure how to write a certain complex query, they can first describe the requirement in natural language and then view the AI-generated SQL statement to learn and understand the syntax and logic of SQL by comparison.
3. Simplify back-office operations
   In some companies' internal backend systems, operations or customer service personnel may need to frequently query user information or order status. Text2Query's pattern can be integrated into internal tools, allowing them to complete data queries by simply asking questions, improving work efficiency and lowering the operation threshold.

QA

1. What languages does Text2Query support?
   Questions in English and Spanish are currently supported.
2. Is it safe to use this tool? Will my database structure be compromised?
   The tool is secure. It has a "privacy-first" design, and all data processing, including the structure of the database you upload and the questions you type, runs locally in your browser and is not uploaded to any external server.
3. How accurate are the generated SQL and MongoDB queries?
   The accuracy depends heavily on how clear and complete the database structure (schema) you provide is. If the structure file provided accurately reflects the table and field relationships of the database, the accuracy of the query statements generated by AI will be very high.
4. Is this tool free?
   Yes, according to available information, Text2Query is currently free to use.