Free online SQL Mock Query: execute SQL statements in the browser with no database required. Supports CREATE, INSERT, and SELECT for practicing query syntax. All local processing.
TL;DR: SQL mock engine with users/orders/products sample tables and SELECT/JOIN/aggregate support.
For local tools, open DevTools → Network and search your input — it should not appear in requests.
Next steps
Usage Guide
Practice SELECT/JOIN/GROUP BY on built-in mock tables in the browser. Teaching engine only — not a production database.
1. Run a query
Destructive SQL is rejected; this page is for read queries.
- Inspect Mock Schema.
- Edit the SELECT.
- Read the grid or error + timing.
2. Practice path
- Single-table filters.
- JOIN users to orders.
- Aggregations with GROUP BY.
- ORDER BY / LIMIT.
3. Coverage
Everyday SELECT features work; full DDL/DML, vendor functions, and procedures do not.
4. Vs real DBs
- Dialects differ — verify on the target engine.
- Mock cardinality is not production.
- Use before interviews, then switch to the real dialect.
5. Pair tools
- SQL formatter.
- csv-sql for INSERTs.
- Mock data generator.
6. Privacy
Local persistence only; keep real schemas out of demos.
FAQ
They persist in a browser-local storage key and are never uploaded — reopen the page to continue practicing, and clearing site data removes them for good.
Three mock tables — users, orders, and products — preloaded with sample data. Expand the Schema panel first to check column names and sample values before writing your query.
Everyday SELECT, INNER/LEFT JOIN, WHERE (comparisons, AND/OR, LIKE, IS NULL), GROUP BY, COUNT/SUM/AVG/MIN/MAX, ORDER BY, and LIMIT including MySQL-style offset,count. Write operations such as DELETE, UPDATE, and DDL are rejected with a clear message.
Misspelled table or column names raise Unknown table or an empty column, so check the Schema panel first. An empty result is not necessarily a broken engine — the classic causes are a reversed JOIN key (id vs user_id) or a WHERE clause that filters out every row.
No. It is a teaching engine: window functions, stored procedures, transactions, permissions, and vendor dialect functions are out of scope — and the same SQL can already differ between MySQL and Postgres in quoting, LIMIT, and date functions. Re-validate critical logic on the target database.
Start with a single table (SELECT, WHERE, ORDER BY, LIMIT), then join users and orders on id/user_id, then GROUP BY status on orders with COUNT/SUM. When a long query will not run, pass it through SQL formatting to check brackets and commas; for more data, pair it with a mock data generator and CSV-to-INSERT conversion.
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