SQL Datediff

Galaxy Glossary

How do I calculate the difference between two dates in SQL?

The DATEDIFF function in SQL calculates the difference between two dates based on a specified unit of time, like days, months, or years. It's crucial for tasks involving date arithmetic and analysis.

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Description

Table of Contents

The `DATEDIFF` function is a fundamental SQL function used to determine the difference between two dates. It's incredibly useful for various data analysis tasks, such as calculating the duration of a project, determining the age of a customer, or tracking the time elapsed between events. The function takes three arguments: the first date, the second date, and the time unit for the difference calculation. Crucially, the result is an integer representing the difference in the specified unit. For example, `DATEDIFF(day, '2023-10-26', '2023-11-15')` will return the number of days between October 26th and November 15th, 2023. Understanding the different time units is key to using `DATEDIFF` effectively. Units like 'year', 'quarter', 'month', 'day', 'week', 'hour', 'minute', and 'second' are commonly used. The specific unit you choose depends on the type of analysis you're performing. For instance, if you need to calculate the number of months between two dates, you'd use the 'month' unit. This function is highly versatile and can be used in various SQL dialects, including MySQL, PostgreSQL, SQL Server, and Oracle, with minor syntax variations.

Why SQL Datediff is important

The `DATEDIFF` function is essential for any SQL application dealing with time-based data. It allows for precise calculations of time intervals, enabling tasks like reporting, analysis, and data manipulation involving dates and times. This function is crucial for tasks like calculating customer tenure, project durations, and identifying trends over time.

SQL Datediff Example Usage


WITH CustomerOrders AS (
    SELECT
        customer_id,
        order_id,
        order_date
    FROM
        orders
    WHERE
        order_date BETWEEN '2023-01-01' AND '2023-03-31'
),
HighValueCustomers AS (
    SELECT
        customer_id,
        SUM(order_total) AS total_spent
    FROM
        CustomerOrders co
    JOIN
        orders o ON co.order_id = o.order_id
    GROUP BY
        customer_id
    HAVING
        SUM(order_total) > 1000
)
SELECT
    c.customer_name,
    hvc.total_spent
FROM
    customers c
JOIN
    HighValueCustomers hvc ON c.customer_id = hvc.customer_id;

SQL Datediff Syntax



Common Mistakes

Frequently Asked Questions (FAQs)

Which time units does SQL DATEDIFF support and when should I use each?

DATEDIFF can return gaps in year, quarter, month, week, day, hour, minute, or second. Choose the unit that aligns with the question you’re answering: use year or month for customer age or subscription tenure, week or day for cohort analysis, and hour/minute/second for real-time event latency. Because the result is always an integer, DATEDIFF cleanly expresses whole-unit differences without decimal rounding.

Does DATEDIFF work the same in MySQL, PostgreSQL, SQL Server, and Oracle?

Not exactly. In SQL Server you call DATEDIFF(unit, start_date, end_date). MySQL has a two-argument DATEDIFF that returns days only; for other units you switch to TIMESTAMPDIFF(unit, start, end). PostgreSQL has no built-in DATEDIFF function—you subtract timestamps or use AGE(), then extract the desired part. Oracle also relies on date arithmetic: subtracting dates gives days, while MONTHS_BETWEEN returns months and NUMTODSINTERVAL converts to other units. Knowing each dialect’s quirks prevents off-by-one errors in production.

How can Galaxy help me write and share DATEDIFF-based analyses faster?

Galaxy’s AI copilot autocompletes correct DATEDIFF (or the dialect-specific equivalent) based on your connected database, highlights invalid units, and even rewrites queries if you switch from, say, SQL Server to PostgreSQL. Once the query is vetted, you can “Endorse” it inside a Galaxy Collection so teammates stop pasting ad-hoc SQL in Slack. The result: faster authoring, fewer syntax errors, and a single source of truth for date-difference logic.

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