How to calculate the difference between two dates in ClickHouse

Learn how to calculate the difference between two dates in ClickHouse using the powerful date_diff function.

Photo: Propel

Discover the power of ClickHouse's date functions to manipulate dates with precision and ease

What is the date_diff function?

ClickHouse provides a range of powerful date and time functions that help you manipulate date and time data types in various ways. The date_diff function is a versatile function that enables you to calculate the differences between two dates or timestamps.

The date_diff function has the following syntax,

date_diff('<unit>', <startdate>, <enddate>)

where

unit is the interval for the result, such as “day”, “hour”, “minute”, “second”, etc.
startdate is the first time value to subtract (the subtrahend).
enddate is the second time value to subtract from (the minuend).

How to calculate the difference between two dates in ClickHouse SQL

You can calculate the difference between two dates in ClickHouse using the date_diff function.

For example, if you want to calculate the difference in days between two dates, the syntax would be:

SELECT date_diff('day', toDate('2021-12-29'), toDate('2022-01-01'))

This would return the number of days between December 29, 2021 and January 1, 2022.

Example: TacoSoft date manipulation

Let's look at an example using TacoSoft, our imaginary SaaS app to manage taquerias. Suppose you have a table called orders with the following columns:

order_id: Unique identifier for each order.
order_date: The date when the order was placed.
customer_id: Unique identifier for each customer.

Your task is to retrieve a list of all orders and the number of days between the order date and a specific date. In this case, let's say you want to find the number of days between the order date and April 14, 2023. You can use the date_diff function to calculate the difference between two dates in ClickHouse and achieve this goal.

Here is the SQL query for this task:

SELECT
  order_id,
  order_date,
  customer_id,
  date_diff('day', order_date, toDate('2023-04-14')) as days_diff
FROM
  orders;

This query would return all the rows in the orders table along with the number of days between the order date and April 14, 2023.

Advanced Example: Calculating Customer Retention with ClickHouse SQL

For a more advanced application of the date_diff function, let's look at how you can use it to calculate customer retention in our imaginary SaaS app, TacoSoft.

Suppose you want to find out how many days it has been since a customer's last order. This information can be useful for understanding customer retention and identifying customers who may be at risk of churning.

To do this, you need to calculate the difference between the current date and the maximum order_date for each customer_id. Here's how you can do this with the date_diff function:

SELECT
  customer_id,
  date_diff('day', MAX(order_date), toDate('2023-04-14')) AS days_since_last_order
FROM
  orders
GROUP BY
  customer_id;

In this query, the MAX(order_date) function retrieves the most recent order_date for each customer_id. The date_diff function then calculates the difference in days between this date and April 14, 2023.

This gives you a list of all customers and the number of days since their last order, which can be a valuable tool in your customer retention strategy.

Build faster with Propel: A Serverless Clickhouse for developers

At Propel, we offer a fully managed ClickHouse service that allows you to focus more on drawing insights from your data and less on infrastructure management. Propel provides an API for data access, React components, and built-in multi-tenant access controls, making it easier and faster for you to build data-intensive applications.

You can connect your own ClickHouse with Propel, whether it's self-hosted or on the ClickHouse Cloud, or take advantage of our fully managed serverless cloud.

Connect your own ClickHouse

✅ Works with self-hosted ClickHouse.
✅ Works with ClickHouse Cloud.
✅ Full control of your ClickHouse deployment.
✅ Data stays in your infrastructure.
✅ Data is encrypted in transit.
✅ Only pay for data passthrough.

Read the docs

Fully managed serverless cloud

✅ Ingest data from any data source.
✅ No infrastructure to manage or scale.
✅ Serverless auto-scaling.
✅ Mission-critical availability.
✅ Unlimited storage.
✅ Data is encrypted at rest and in transit.
✅ Only pay for the storage you use and queries you make.

Read the docs

Conclusion

In this post, we explored ClickHouse's date_diff function to calculate the difference between two dates or timestamps. By using this function, you can easily perform date difference calculations. This tool can be valuable for filtering and analyzing time-based data in your ClickHouse data warehouse.

ClickHouse offers many other date and time functions to help you manipulate and work with date and time data types. Don't hesitate to explore the official ClickHouse documentation to learn more about these functions and how to use them effectively.

Heading 1

Heading 2

Heading 3

Heading 4

Heading 5

Heading 6

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.