Free Text to SQL Generator - Turn Plain English Into Queries

Natural Language to SQL for MySQL, PostgreSQL, SQLite, and More

Text to SQL converts plain-English descriptions into accurate, executable database queries using advanced AI trained on SQL syntax, database patterns, and query optimisation. Just describe what data you need and the AI writes the correct SELECT, JOIN, GROUP BY, or subquery - No SQL knowledge required to get started.

Whether you need a quick SELECT with a WHERE clause or a complex multi-table JOIN with aggregations, our generator handles every query type. It reads your schema context, applies the right syntax for your target database, and returns production-ready SQL. For documentation, pair this with our Outline Generator, or use our AI Humanizer to write clear explanations of complex logic. No account required.

Key Capabilities

• Multi-Database Support - MySQL, PostgreSQL, SQLite, SQL Server, Oracle - syntax optimised for each platform.
• All Query Types - SELECT, INSERT, UPDATE, DELETE, JOINs, subqueries, aggregations, window functions.
• Always Free - No subscription, no token limits, no hidden costs. Free SQL generation for everyone.
• No Registration Required - Start generating SQL queries immediately. No account needed.

Query Types We Generate

Why Use Our Text to SQL Generator?

Stop memorising SQL syntax. Describe what you need and let the AI handle the rest.

Generate Production-Ready SQL from a Single Sentence

Paste your table structure, describe what you need, and get an optimised query back - Ready to run.

Stop Looking Up Syntax. Start Describing Results.

Most SQL errors aren't logic errors - They're syntax errors. Wrong JOIN order, missing GROUP BY, date function differences between databases. Our generator takes the syntax burden off your plate. Describe the result you want, paste your table structure if needed, and get back a query you can run immediately. It works for one-off data pulls, report queries, and production application code.

• Schema-Aware Generation - Paste your CREATE TABLE statements and the generator uses your exact column names and types.
• Query Refining - Not quite right? Describe the change and the AI adjusts the query without starting over.
• Performance Hints - For complex queries, the generator flags indexes that would speed up the query and explains why.
• Cross-Platform Output - Ask for the same logic in MySQL, PostgreSQL, or SQLite and get the dialect-correct version each time.

Build Complex Queries Through Conversation

Start simple, then add conditions, joins, and filters step-by-step. The AI remembers your schema throughout.

Iterate on Queries Like You'd Iterate on Code

Real SQL work is iterative. You start with a basic query, run it, realise you need an extra filter, add a JOIN, check the result. Our interactive mode matches that workflow. Describe the initial query, then refine it one step at a time. The AI tracks your schema and context so you don't have to repeat yourself with every message.

• Schema Context Retention - Describe your tables once. The AI remembers and uses them throughout the conversation.
• Incremental Refinement - Add WHERE clauses, filters, sorting, and JOINs to an existing query without restarting.
• Explanation on Demand - Ask "why does this JOIN work?" and get a plain-English walkthrough of the query logic.
• Instant Debugging - Paste a broken query and a description of the expected result - the AI diagnoses and fixes it.

Optimised SQL for Every Major Database

Each database has its own dialect. Our generator knows the differences and applies the right syntax automatically - 100% FREE.

SQL Dialect Support - MySQL, PostgreSQL, SQLite and More

Specify your database and the AI generates syntax that works in your exact environment.

Tell the AI which database you're using and it automatically applies the correct syntax for that dialect.

Natural Language to SQL - Real Conversions

From simple queries to complex analytics - see the SQL generated from plain English descriptions.

SELECT
    c.customer_id,
    c.name,
    c.email,
    COUNT(o.id)          AS order_count,
    SUM(o.total_amount)  AS total_spend
FROM customers c
JOIN orders o ON o.customer_id = c.customer_id
WHERE o.created_at >= CURRENT_DATE - INTERVAL 30 DAY
GROUP BY c.customer_id, c.name, c.email
HAVING COUNT(o.id) > 3
ORDER BY total_spend DESC;

WITH ranked_products AS (
    SELECT
        category,
        product_name,
        SUM(quantity * unit_price) AS revenue,
        RANK() OVER (
            PARTITION BY category
            ORDER BY SUM(quantity * unit_price) DESC
        ) AS rank_in_category
    FROM order_items oi
    JOIN products p ON p.id = oi.product_id
    GROUP BY category, product_name
)
SELECT category, product_name, revenue, rank_in_category
FROM ranked_products
WHERE rank_in_category <= 5
ORDER BY category, rank_in_category;

CREATE TABLE authors (
    id         SERIAL PRIMARY KEY,
    name       VARCHAR(120) NOT NULL,
    email      VARCHAR(200) UNIQUE NOT NULL,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

CREATE TABLE posts (
    id          SERIAL PRIMARY KEY,
    author_id   INT NOT NULL REFERENCES authors(id) ON DELETE CASCADE,
    title       VARCHAR(300) NOT NULL,
    slug        VARCHAR(320) UNIQUE NOT NULL,
    body        TEXT,
    published   BOOLEAN DEFAULT FALSE,
    published_at TIMESTAMPTZ,
    created_at  TIMESTAMPTZ DEFAULT NOW()
);

CREATE TABLE tags (
    id   SERIAL PRIMARY KEY,
    name VARCHAR(80) UNIQUE NOT NULL
);

CREATE TABLE post_tags (
    post_id INT REFERENCES posts(id) ON DELETE CASCADE,
    tag_id  INT REFERENCES tags(id)  ON DELETE CASCADE,
    PRIMARY KEY (post_id, tag_id)
);

WITH monthly_revenue AS (
    SELECT
        DATE_TRUNC('month', created_at) AS month,
        SUM(total_amount)               AS revenue
    FROM orders
    WHERE status = 'completed'
    GROUP BY 1
)
SELECT
    month,
    revenue,
    LAG(revenue) OVER (ORDER BY month)             AS prev_month_revenue,
    ROUND(
        (revenue - LAG(revenue) OVER (ORDER BY month))
        / NULLIF(LAG(revenue) OVER (ORDER BY month), 0) * 100,
        2
    )                                               AS mom_growth_pct
FROM monthly_revenue
ORDER BY month DESC;

Frequently Asked Questions

Common questions about our free text-to-SQL generator.