Filtering data based on a date range is an extremely common task when analyzing data in SQL. The BETWEEN operator provides a convenient way to select rows within a start and end date.

In this comprehensive guide, we‘ll cover everything you need to know to leverage the power of BETWEEN for querying data between two dates in SQL.

Understanding BETWEEN for Date Filters

The BETWEEN operator allows you to filter rows where a value falls within a specified range. Here is the basic syntax:

SELECT columns
FROM table  
WHERE date_column BETWEEN start_date AND end_date;

This queries for rows where date_column is greater than or equal to start_date and less than or equal to end_date.

Some key characteristics of BETWEEN:

  • Inclusive range – start and end values are included
  • Works for dates, numbers, text
  • Simpler than chaining multiple comparisons

Overall, BETWEEN provides a cleaner way to filter dates than stringing together a bunch of > and < comparisons.

In terms of dates, you need to format your start and end dates consistently. The standard format is ‘YYYY-MM-DD‘.

Let‘s move on to some examples of using BETWEEN for filtering dates.

Filtering by Date Ranges: Practical Examples

BETWEEN becomes extremely powerful paired with date data to analyze trends over time. Here are some common use cases:

  • Filter orders for month-to-date (MTD) reports
  • Analyze weekly or monthly user signup trends
  • View rolling 28-day retention cohorts

Let‘s go through some detailed examples of using BETWEEN to filter data by date ranges.

We‘ll start by creating a sample orders table with some data:

CREATE TABLE orders (
  order_id INT,  
  order_date DATE,
  customer_id INT  
);

INSERT INTO orders
VALUES
  (1, ‘2023-01-01‘, 123),
  (2, ‘2023-01-18‘, 456),
  (3, ‘2023-01-04‘, 789),
  (4, ‘2023-01-11‘, 213);

This contains order data with order_date spanning January 2023.

Example 1: Basic Date Range Filter

Let‘s start with a simple example fetching all orders between 1/4/2023 and 1/11/2023: 

SELECT *
FROM orders
WHERE 
  order_date BETWEEN ‘2023-01-04‘ AND ‘2023-01-11‘;

This returns orders #3 and #4 based on the date range filter. Simple to filter date ranges!

Example 2: Year-over-Year Analysis

A common analytics use case is comparing performance between years. For example, we could analyze year-over-year (YoY) order totals like this:

SELECT 
  YEAR(order_date) AS order_year,  
  SUM(order_total) AS total_orders
FROM orders
WHERE
  order_date BETWEEN ‘2022-01-01‘ AND ‘2023-01-31‘
GROUP BY 1;

By filtering between 1/1/2022 and 1/31/2023 before grouping, we can easily compare 2022 vs. 2023 order totals. BIG YoY growth!

This is much cleaner than trying to use multiple YEAR() checks in the WHERE clause.

Example 3: Date Range With Other Filter Conditions

A great aspect of BETWEEN is combining it with other filter criteria. You can filter based on a date window AND/OR other conditions.

Let‘s filter for repeat customers in Dec 2022:

SELECT customer_id, COUNT(*) AS num_orders 
FROM orders
WHERE
  order_date BETWEEN ‘2022-12-01‘ AND ‘2022-12-31‘  
  AND customer_id IN (
    SELECT customer_id 
    FROM orders
    WHERE order_date < ‘2022-12-01‘
)
GROUP BY 1;

By adding an exists check on past orders, we can view recent repeat purchasers alongside our date filter.

As you can see, the date range capabilities of BETWEEN pair nicely with other filtering options.

Now that we have some queries under our belt, let‘s compare BETWEEN to other date range constructs.

BETWEEN vs. Other Date Range Methods

While BETWEEN makes querying date ranges easy, there are a few other options:

  • Using AND to chain multiple comparison operators
  • The BETWEEN syntactic equivalent

Let‘s compare them to understand when to use each approach.

BETWEEN vs. Chained Comparison Operators

A common pre-BETWEEN approach for filtering dates was chaining a bunch of > and < together:

SELECT *
FROM orders
WHERE 
  order_date >= ‘2023-01-01‘
  AND order_date <= ‘2023-02-01‘;

This allows you to define an upper and lower bound for a custom date range, similar to BETWEEN.

However, there are some downsides:

  • Verbose – more code
  • Harder to visualize the range
  • Slower for the optimizer
  • More opportunities for logic errors

Overall, BETWEEN provides cleaner syntax for date ranges.

BETWEEN vs. Equivalent Constructs

An alternative way to express a BETWEEN filter is by using equivalent syntax with comparison operators:

SELECT *
FROM orders 
WHERE 
  order_date >= ‘2023-01-01‘
  AND order_date  <= ‘2023-02-01‘

We are simply substituting the BETWEEN for the same >= AND <= logic.

So when should you use each approach?

Generally, prefer simplicity with BETWEEN. However, complex queries may run faster with the comparison construct variant.

Testing with EXPLAIN can identify performance differences. Pay attention to:

  • Number of key lookups
  • Range scanned on indexes

If performance is no issue, I suggest sticking with BETWEEN for code clarity.

Best Practices for Querying Between Dates

When filtering date ranges with BETWEEN, follow these best practices:

  • Use consistent date formats – Stick to YYYY-MM-DD dates
  • Validate date ranges – Ensure the start <= end
  • Index date columns – Speed up range scans significantly
  • Test complex queries – Compare plans to equivalent logic
  • Watch out for time components – Dates have times too!

Following those tips will help optimize date filtering performance.

Let‘s conclude by summarizing the key points around using SQL BETWEEN with dates.

Summary

Here is a quick recap of what we covered in this guide:

  • BETWEEN allows querying data between a start and end value
  • Works great for filtering date ranges when formatted as YYYY-MM-DD
  • Very useful for analyzing trends over time
  • Can combine date filters with other WHERE criteria
  • Provides simpler syntax than chaining multiple comparisons
  • Make sure to index dates for good performance

Filtering by a date range is an extremely common task for data analysis. Using SQL‘s BETWEEN operator makes it easy to query data between two dates.

Now you have all the knowledge to leverage BETWEEN for investigating trends spanning periods of time in your data warehouse, application, analytics, and reporting.

Put this powerful date range querying capability to work across all your SQL-based analysis!

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