AI SQL Query Generator

What Is an AI SQL Generator and How Does It Work?

An AI SQL Generator is an intelligent tool that converts plain-English descriptions into accurate, ready-to-run SQL queries — instantly and for free. Instead of memorising complex syntax for SELECT, JOIN, GROUP BY, or subqueries, you simply describe what data you need and the AI writes the query for you.

Our free SQL generator online is powered by the Groq llama-3.3-70b-versatile large language model — one of the fastest and most capable AI models available. It understands your natural-language request, infers the correct table relationships, and produces clean, optimised SQL that works with MySQL, PostgreSQL, SQLite, MS SQL Server, and Oracle databases.

Whether you are a data analyst pulling business reports, a backend developer prototyping queries, a student learning database concepts, or a non-technical founder exploring your data — this AI SQL query generator removes the learning curve and saves hours of manual work every day.

Key Features of Our Free SQL Generator

How to Use the AI SQL Generator — Step-by-Step Guide

1. 1

   Describe your data need in plain English

   In the prompt box, type what you want to retrieve, update, or delete. Be as specific as possible — mention table names if you know them, filters, sorting order, and any conditions.

2. 2

   Select the target SQL dialect

   Choose your database engine from the dropdown — MySQL, PostgreSQL, SQLite, MS SQL Server, or Oracle. The AI adjusts syntax, functions, and data types accordingly.

3. 3

   Click "Generate SQL Query"

   Hit the generate button. The Groq-powered AI model processes your request and returns a clean, formatted SQL query in under 2 seconds — faster than any human developer.

4. 4

   Review, copy, and run the query

   Read through the generated SQL, click "Copy", and paste it into your database client or application. If you need adjustments, refine your prompt and regenerate — it's free and unlimited.

Example — Sample AI SQL Generator Output

Prompt entered: "Show me the names and total revenue of all customers who placed more than 3 orders in the last 6 months, sorted by revenue descending."

SELECT
    c.customer_name,
    SUM(o.total_amount) AS total_revenue
FROM customers c
INNER JOIN orders o ON c.customer_id = o.customer_id
WHERE o.order_date >= DATE_SUB(NOW(), INTERVAL 6 MONTH)
GROUP BY c.customer_id, c.customer_name
HAVING COUNT(o.order_id) > 3
ORDER BY total_revenue DESC;

The AI correctly identified the need for an INNER JOIN, a date filter, GROUP BY with HAVING for the count condition, and DESC sorting — all from a single plain-English sentence.

Supported Use Cases & Examples

Our AI SQL generator handles a wide range of real-world database tasks. Below are four concrete examples showing the kind of queries it produces across different databases and complexity levels.

SELECT
    cat.category_name,
    SUM(oi.quantity * oi.unit_price)          AS total_revenue,
    AVG(o.order_total)                         AS avg_order_value
FROM categories cat
INNER JOIN products   p  ON p.category_id   = cat.category_id
INNER JOIN order_items oi ON oi.product_id  = p.product_id
INNER JOIN orders      o  ON o.order_id     = oi.order_id
WHERE YEAR(o.created_at) = YEAR(CURDATE())
GROUP BY cat.category_id, cat.category_name
ORDER BY total_revenue DESC;

SELECT
    employee_name,
    department_name,
    salary,
    salary_rank
FROM (
    SELECT
        e.employee_name,
        d.department_name,
        e.salary,
        RANK() OVER (
            PARTITION BY e.department_id
            ORDER BY e.salary DESC
        ) AS salary_rank
    FROM employees e
    INNER JOIN departments d ON d.department_id = e.department_id
) ranked
WHERE salary_rank <= 3
ORDER BY department_name, salary_rank;

SELECT
    u.user_id,
    u.email,
    u.created_at
FROM users u
WHERE u.status     = 'active'
  AND u.created_at >= DATE('now', '-90 days')
  AND u.user_id   NOT IN (
      SELECT DISTINCT customer_id FROM orders
  )
ORDER BY u.created_at DESC;

WITH OrgChart AS (
    -- Anchor: start with the CEO (no manager)
    SELECT employee_id, employee_name, manager_id, 0 AS depth
    FROM   employees
    WHERE  manager_id IS NULL

    UNION ALL

    -- Recursive: join each employee to their manager
    SELECT e.employee_id, e.employee_name, e.manager_id, oc.depth + 1
    FROM   employees e
    INNER JOIN OrgChart oc ON oc.employee_id = e.manager_id
)
SELECT employee_id, employee_name, depth
FROM   OrgChart
ORDER  BY depth, employee_name
OPTION (MAXRECURSION 10);