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How to Validate SQL Queries Online: Step-by-Step Tutorial

By Bill Crawford ยท February 27, 2026 ยท SQL  ยท  Last updated February 27, 2026

Table of Contents

  1. Step 1: Open the SQL Validator
  2. Step 2: Select Your Dialect
  3. Step 3: Paste Your SQL
  4. Step 4: Click "Validate SQL"
  5. Step 5: Review the Results
  6. Step 6: Try Dialect-Specific Validation
  7. Step 7: Check for Dangerous Queries
  8. Step 8: Share Your Validation
  9. Next Steps
  10. Related Tools & Guides
  11. Related Articles

Step 1: Open the SQL Validator

Go to the SQL Validator page. You will see a code editor area, a dialect selector, and mode tabs for Validate, Format, and Explain. The validator is selected by default.

Step 2: Select Your Dialect

Use the dialect dropdown to select your target database: Generic SQL, PostgreSQL, MySQL, T-SQL (SQL Server), or SQLite. This is important because each dialect has different syntax rules. A query that is valid in PostgreSQL may be invalid in MySQL.

If you are unsure, start with Generic SQL. You can switch dialects and re-validate to see dialect-specific issues.

Step 3: Paste Your SQL

Paste your SQL query into the editor. The editor supports tab indentation and Ctrl+Enter to run the validator. You can also click the "Load Sample" button to try a sample query.

Example Query to Validate

SELECT c.name, COUNT(o.id
FROM customers c
JOIN orders o ON c.id = o.customer_id
WHERE o.status = 'paid'
GROUP BY c.name

This query has a deliberate error โ€” an unclosed parenthesis after COUNT(o.id.

Step 4: Click "Validate SQL"

Click the blue "Validate SQL" button or press Ctrl+Enter. The results panel appears below the editor with a summary badge and a detailed list of errors and warnings.

Step 5: Review the Results

The validator shows:

Fix the reported errors in your SQL and validate again until the result shows green.

Step 6: Try Dialect-Specific Validation

Change the dialect to see different results. For example, this query is valid in PostgreSQL but invalid in MySQL:

SELECT name::text FROM users WHERE name ILIKE '%john%'

With PostgreSQL selected, it passes. Switch to MySQL and you get two errors: :: is not supported and ILIKE is not available.

Step 7: Check for Dangerous Queries

The validator warns about dangerous operations. Try pasting:

DELETE FROM orders

The validator flags this with a warning: "DELETE without WHERE clause โ€” this will delete ALL rows." This is syntactically valid SQL, but almost certainly not what you intended.

Step 8: Share Your Validation

Click the Share button to generate a URL that anyone can open to see the same SQL and validation results. The SQL is encoded in the URL โ€” no server storage is involved.

Ready to validate your own SQL?

Open SQL Validator

Next Steps

After validating your SQL, use the SQL Formatter to clean up the formatting, and the SQL Query Explainer to get a plain English breakdown of what the query does.

Further reading: MySQL โ€” SQL Statement Syntax ยท SQLite โ€” SQL Language Reference

BC
Bill Crawford
Founder, Data Conversion Center

Bill Crawford is a data systems developer and technical founder with over 30 years of professional experience in accounting, finance, and business operations.

He holds a Bachelor’s degree in Accounting and has spent more than three decades working within financial and operational environments. Over the past 10 years, he has been heavily involved in the development, implementation, and refinement of financial and enterprise data systems for both Fortune 500 companies and smaller organizations.

His work bridges finance and technology — combining deep domain knowledge in structured reporting and accounting workflows with hands-on SQL development and database architecture experience.

Bill founded DataConversionCenter.com to build practical, browser-based tools that simplify complex data challenges, including:

Rather than focusing on theoretical examples, his tools and articles are informed by real-world challenges encountered in enterprise reporting systems, financial databases, and operational data environments.

Professional Background
  • Bachelor’s Degree in Accounting
  • 30+ years in accounting and finance
  • 10+ years deeply involved in financial and enterprise systems development
  • Experience supporting Fortune 500 and small-to-mid-sized organizations
  • Hands-on SQL development across relational database platforms

Bill’s mission is to reduce friction in data workflows — particularly for professionals working with structured financial, operational, and reporting data.