This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
SQL Mocker supports two workflows for working with SQL without connecting AI to your real database. First, you can create SQL from natural language queries using a safe schema replica and generated dummy data. This helps you review tables, relationships, filters, and result shape before using the SQL in your real database or reporting tool. Second, you can upload existing SQL to review, refine, troubleshoot, and improve it without exposing production data or database credentials.
I built SQL Mocker because I kept seeing the same problem: people want help writing SQL, but they do not always want an AI tool connecting directly to their real database.
SQL Mocker has two main workflows.
First, you can create SQL using natural language questions using a reviewed schema and generated dummy data. This lets you check tables, columns, relationships, filters, and result shape before using the SQL in your real database or reporting tool.
Second, you can upload existing SQL to review, refine, troubleshoot, and improve it without exposing production data or database credentials.
I’d love feedback from anyone who writes SQL, supports reporting users, or works with tools like Power BI.
A few things I’m especially interested in: - Is the “no direct database connection” workflow clear? - Would schema review before SQL generation be useful in your team? - What would make the SQL review process more trustworthy?
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About SQL Mocker on Product Hunt
“Natural language SQL without database access”
SQL Mocker was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #125 on the daily leaderboard. SQL Mocker supports two workflows for working with SQL without connecting AI to your real database. First, you can create SQL from natural language queries using a safe schema replica and generated dummy data. This helps you review tables, relationships, filters, and result shape before using the SQL in your real database or reporting tool. Second, you can upload existing SQL to review, refine, troubleshoot, and improve it without exposing production data or database credentials.
SQL Mocker was featured in Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and Data & Analytics (5.7k followers) on Product Hunt. Together, these topics include over 183.7k products, making this a competitive space to launch in.
Who hunted SQL Mocker?
SQL Mocker was hunted by FFleury. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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FFleury
Hi Product Hunt,
I built SQL Mocker because I kept seeing the same problem: people want help writing SQL, but they do not always want an AI tool connecting directly to their real database.
SQL Mocker has two main workflows.
First, you can create SQL using natural language questions using a reviewed schema and generated dummy data. This lets you check tables, columns, relationships, filters, and result shape before using the SQL in your real database or reporting tool.
Second, you can upload existing SQL to review, refine, troubleshoot, and improve it without exposing production data or database credentials.
I’d love feedback from anyone who writes SQL, supports reporting users, or works with tools like Power BI.
A few things I’m especially interested in:
- Is the “no direct database connection” workflow clear?
- Would schema review before SQL generation be useful in your team?
- What would make the SQL review process more trustworthy?
Thanks for taking a look.