Trust
Security & Privacy
SQL Mocker is designed to help users work with database structure and SQL while keeping control of database access and query execution in their own hands.
Your Database Stays Under Your Control
SQL Mocker's hosted schema workflow uses database structure supplied by you. The AI does not need a direct connection to your production database. You choose what metadata to provide, review generated SQL, and decide where and when to run it.
Database Credentials
SQL Mocker does not require you to provide your database credentials to the AI in order to generate SQL from schema context. Do not place usernames, passwords, connection strings, tokens, or private keys in prompts, uploads, SQL, or support messages.
Database Metadata
Database metadata describes structure: table and column names, data types, primary keys, foreign keys, relationship information, and schema organisation. This context helps SQL Mocker map questions to real fields and joins without needing the contents of production rows.
Production Data
Database records contain the operational values stored in tables. Schema-based workflows are designed to work from metadata and generated dummy data, so private production rows are not required for SQL generation. A user could still manually submit sensitive content, so review every prompt and upload before sending it.
Metadata Extraction
SQL Mocker generates a metadata extraction script. You inspect and run it in your own database environment, then bring the resulting structural metadata into SQL Mocker. Running that focused script is different from granting the hosted application unrestricted database access.
Table Relationships
SQL Mocker uses primary-key, foreign-key, and relationship metadata already defined by the database where available. You can review or complete unclear connections in the workspace. Relationships created or edited in SQL Mocker do not change relationships in the underlying database.
SQL Execution
Generated SQL is presented for review and copying. In the hosted workflow, you run it in your own database tool using your organisation's credentials, permissions, and change controls. SQL Mocker does not execute that SQL against a live customer database.
User Control
You remain responsible for checking field references, joins, filters, calculations, dialect compatibility, and expected results. Always review generated SQL before running it against a production system, and use appropriate testing and approval processes.