SQL Mocker

SQL Mocker is a browser workspace that turns natural-language questions into SQL using database schema metadata you provide. It suits analysts, consultants, and report builders preparing queries for Power BI or database tools. Its main advantage is a schema-focused workflow that avoids live-database access; its main constraint is that every generated query remains your responsibility to check.

Overview

SQL Mocker builds context from an uploaded schema file, pasted metadata, a schema you construct manually, or results from an extraction script run in your own database. This is a practical way to get query assistance without supplying database credentials or granting the service access to production rows. The trade-off is equally clear: SQL Mocker does not execute queries against your live database. You copy its output into Power BI Desktop or another database tool and run it there, and it does not connect directly to Power BI.

The workspace can generate dummy data from a schema, allowing you to preview likely results and exercise query logic without using production records. Projects sync to your SQL Mocker account and are cached in your device's browser; a backup file can be saved from History to your PC. The security guidance matters for teams handling confidential information: users can manually submit sensitive prompts or uploads, so those inputs need review before submission.

Key features

Schema-led SQL generation

Natural-language requests are interpreted against reviewed schema metadata rather than an opaque connection. SQL Mocker can detect table relationships and lets you inspect, edit, or add them, including links absent from the source metadata. That makes it more useful than a bare text-to-SQL prompt when joins depend on business-specific structure, while still requiring you to correct incomplete or inaccurate metadata.

SQL review and explanation

You can paste or upload existing SQL to have it explained, reviewed, improved, formatted, converted, or troubleshot. The workspace can also map output columns and joins. These functions fit analysts inheriting queries or consultants preparing deliverables, but they are advisory: the maker warns that AI-generated SQL may be wrong, so review, test, and validate before use.

Broad database coverage

The homepage names 17 supported systems: SQL Server, PostgreSQL, MySQL, Oracle, SQLite, MariaDB, Snowflake, BigQuery, Amazon Redshift, Databricks, SAP HANA, IBM Db2, Teradata, Microsoft Access, ClickHouse, DuckDB, and MongoDB. Coverage is valuable for mixed-stack teams, although execution still happens in your own database environment.

Pricing

SQL Mocker uses a freemium model. Explore costs nothing for one user, 50 AI queries total, and five saved projects; no credit card is required. It is a sensible way to evaluate the schema workflow, but the lifetime query allowance is small for regular production work.

Starter is $10 a month, billed $10/month, for one user, 100 AI queries per month, and 20 saved projects. Pro is $20 a month, billed $20/month, with 300 monthly queries and 100 saved projects for one user. Business is $39 a month, billed $39/month, for one user, 1,000 monthly queries, and custom saved projects. Starter, Pro, and Business are coming soon and require joining a waitlist, so these are not immediately usable subscriptions.

Enterprise uses custom pricing and custom query and saved-project limits for multiple users; it is also coming soon via waitlist. There is no published multi-seat price, making it a planning conversation rather than a ready procurement option.

Platforms

SQL Mocker is delivered as a web application with cloud deployment. It supports schema-led work across the 17 database systems named above, but it does not provide direct Power BI integration or live-database execution.

Who it's for

Choose SQL Mocker if you are an analyst, consultant, or report builder who needs to turn business questions into draft SQL, inspect joins, or prepare statements for Power BI while keeping database credentials out of the service. It is also useful for reviewing inherited SQL and previewing logic with dummy data. It is a poor fit for teams expecting an application to connect to production, run queries automatically, or guarantee executable SQL without human review.

Pros and cons

• Pros: schema metadata can be supplied without credentials or live customer-database access; relationships are reviewable and editable; dummy-data previews support safer logic checks; SQL explanation, formatting, conversion, troubleshooting, and column/join mapping cover more than first-draft generation; support spans 17 named database systems.
• Cons: output can be incorrect and must be tested by the user; there is no direct Power BI connection or in-app execution; sensitive prompts and uploads remain a user privacy responsibility; the free tier allows only 50 total AI queries and five projects; paid tiers are waitlisted and limited to one user until Business, with Enterprise pricing custom.

Alternatives

For an open-source local installation, Natural Language SQL is free under GPL-3.0 and runs across API, Linux, macOS, self-hosted, and web environments. Outerbase AI is the better choice when you need a broader team-oriented product: its free plan supports up to five users, one base, 10 EZQL queries per month, three saved queries, and one dashboard for transactional databases.

NatureQuery suits a lighter web/API workflow with a free allowance of 50 queries per month, one database connection, Excel and CSV export, and 30 days of query history. QueryPlane is worth considering for self-hosted deployments, with a free plan covering up to three apps, one database connection, 50 AI prompts per month, and community support.

Savvina AI offers a free community plan for one user with PostgreSQL and MySQL, unlimited connections, and GitHub community support. SQLer is an alternative for higher-volume NL2SQL quotas, starting with 50 queries per month free and a $199/month Lift-Off plan for 2,500 queries. Wren AI provides an open-source context engine and cloud options. IDERA AI SQL Query Generator is a free web option with limits applying.

For a wider shortlist, see AI SQL Generators.

Verdict

SQL Mocker is a strong fit for professionals who want schema-aware SQL drafting and review without connecting a customer database, especially when dummy-data previews and editable relationships matter. Choose it for controlled preparation before Power BI or database execution. Look elsewhere if you need live querying, direct Power BI integration, ready-to-buy team plans, or a guarantee that generated SQL is correct without substantial validation.