🗄️ SQL examples

BETWEEN Examples in SQL

Filter values inside a range such as dates, amounts or scores. This page gives you the syntax, five practical examples, common mistakes, and copy-ready SQL you can adapt.

Updated 2026-06-125 practical examplesCopy-ready SQL

What BETWEEN does

Filter values inside a range such as dates, amounts or scores. SQL syntax can vary by database, but the pattern below is a useful starting point for reports and analysis.

Syntax or pattern

SELECT * FROM table_name WHERE column_name BETWEEN value1 AND value2;
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5 practical examples

1

Use BETWEEN in a sales report

Apply the BETWEEN pattern to a sales table.

-- BETWEEN example for sales SELECT customer_id, order_date, total_amount FROM orders WHERE total_amount > 100;

This shows how the BETWEEN pattern can support a simple sales analysis.

2

Use BETWEEN for customers

Apply the BETWEEN pattern to customer records.

-- BETWEEN example for customers SELECT customer_id, email, status FROM customers WHERE status = 'Active';

This is useful when customer records need filtering, labeling or summarizing.

3

Use BETWEEN for products

Apply the BETWEEN pattern to product or inventory data.

-- BETWEEN example for products SELECT product_id, product_name, category FROM products;

Product tables are good practice data for this SQL pattern.

4

Use BETWEEN for monthly reporting

Apply the BETWEEN pattern to a monthly reporting query.

-- BETWEEN example for monthly reporting SELECT DATE_TRUNC('month', order_date) AS month, SUM(total_amount) AS sales FROM orders GROUP BY DATE_TRUNC('month', order_date);

This turns row-level transactions into a report-friendly result.

5

Use BETWEEN during data checks

Apply the BETWEEN pattern to find data quality issues.

-- BETWEEN example for data checks SELECT customer_id, COUNT(*) AS records FROM orders GROUP BY customer_id HAVING COUNT(*) > 1;

This is a useful pattern for auditing data before building a report.

Common mistakes to avoid

  • Forgetting that SQL dialects vary across PostgreSQL, SQL Server, MySQL, BigQuery and SQLite.
  • Using SELECT * in production reports when only a few columns are needed.
  • Not checking join keys, duplicate rows or NULL values before trusting results.

FAQ

Will this SQL work in every database?

The idea is portable, but function names and date syntax may vary. Check your database dialect if a function is not recognized.

Should I use this in a report query?

Yes, if the pattern matches the business question and you have checked filters, joins and row counts.

Why does my result have too many rows?

The most common reasons are duplicate join keys, missing filters or grouping at the wrong level of detail.

💡 Useful resources

Here are some ideas for you

Optional resources that may help if you are learning SQL, building reports, writing queries or improving your data workflow.

  • 📘
    SQL books for beginners

    Practice query patterns with structured examples and exercises.

    See ideas
  • 🧱
    Database design books

    Understand tables, keys, relationships and why joins behave the way they do.

    See ideas
  • ⌨️
    Mechanical keyboards

    Useful if you write queries, code and documentation for long work sessions.

    See ideas
  • 🖥️
    External monitors

    View query editor, result grid and documentation side by side.

    See ideas
  • 📒
    Developer notebooks

    Sketch table relationships, query logic and report ideas before coding.

    See ideas
  • 💡
    Desk lamps

    Keep your workspace comfortable while studying or debugging queries.

    See ideas

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