SQL Server functions – SQL Server Guides

SQL RANK vs DENSE_RANK

Bijay Kumar Sahoo — Fri, 12 Jun 2026 10:24:42 +0000

In this comprehensive tutorial, I will guide you through a deep-dive exploration of SQL RANK and DENSE_RANK. We will break down their mathematical differences, analyze their evaluation mechanics inside the query optimizer, dissect the role of the PARTITION BY clause, and establish foundational best practices.

SQL RANK vs DENSE_RANK

The Genesis of Analytic Rank: Understanding Window Functions

Before we directly compare RANK and DENSE_RANK, we must establish the underlying computational engine that drives them: Window Functions (also known as analytic or OLAP functions).

In standard SQL manipulation, a traditional query evaluates data in one of two configurations:

Row-by-Row Evaluation: Processing single records independently using scalar operations.
Aggregated Blocks: Collapsing multiple rows into a single summary output row using a GROUP BY clause.

Window functions offer a powerful hybrid capability. They calculate an aggregate-style value across a specific subset of records—known as a window—while fully preserving the distinct identity of every individual row in the final result set.

Ranking functions operate strictly within this window environment. They instruct the query optimizer to scan a designated set of rows, sort them according to a specified data attribute, and assign a sequential integer to each row.

To invoke this window tracking mechanic, ranking cmdlets must always be paired with the OVER clause. If you attempt to call RANK() or DENSE_RANK() as a standalone scalar function without an OVER specification, the query compiler will immediately reject the statement with a syntax compilation error.

Deconstructing SQL RANK: The Gap-Inducing Architecture

The standard RANK function calculates the rank of each row within your ordered partition based on a specified value expression. However, its most critical defining characteristic is how it behaves when it encounters ties—multiple rows containing the exact same values for the sorting criteria.

When RANK encounters a tie, it assigns the exact same ranking number to all identical rows in that tied set. Then, it introduces a gap into the sequential ranking chain. The size of the gap is exactly equal to the number of tied rows minus one.

Let us look at this structural mechanic conceptually:

Imagine you are evaluating a performance leaderboard of corporate branch offices based in Chicago, Atlanta, and Boston.
The top-performing branch takes rank 1.
The next two branches have identical sales metrics. They both tie for rank 2.
Because two records shared rank 2, the standard RANK engine skips a position entirely. The subsequent distinct record is immediately jumped to rank 4.

I classify RANK as a “competition-style” ranking engine. It mirrors the traditional logic of Olympic sports: if two athletes tie for the silver medal, there is no bronze medal awarded; the next finisher drops straight down to fourth place.

Deconstructing SQL DENSE_RANK: The Gapless Continuum

The DENSE_RANK function addresses ties using a completely different mathematical continuum. Like its counterpart, when DENSE_RANK encounters identical values within an ordered partition, it assigns the exact same integer to all matching rows in that tied set.

However, the divergence occurs on the next distinct row. DENSE_RANK completely eliminates gaps from the ranking sequence. Regardless of how many rows tied for a specific position, the very next rank value in the chain is always the immediate next consecutive integer.

Let us apply this logic to our previous corporate leaderboard concept:

The top-performing branch takes rank 1.
The next two branches tie for rank 2.
The subsequent distinct record is assigned rank 3.

The sequence remains completely dense and unbroken (1, 2, 2, 3, 4…). I call DENSE_RANK a “dense-tiering” engine. It cares exclusively about the number of distinct value classifications that exist above a row, completely ignoring the total count of duplicate rows that occupy those higher tiers.

SQL RANK vs DENSE_RANK: Direct Comparison Matrix

To solidify your understanding of these behaviors, let us contrast their core characteristics side-by-side in an authoritative technical reference table.

Architectural Parameter	SQL RANK Function	SQL DENSE_RANK Function
Handling of Ties	Assigns identical ranks to matching rows; skips subsequent values.	Assigns identical ranks to matching rows; preserves strict consecutive continuity.
Sequence Behavior	Gap-inducing (e.g., 1, 2, 2, 4, 5…)	Gapless (e.g., 1, 2, 2, 3, 4…)
Mathematical Basis	Tied rank reflects the true number of rows preceding it + 1.	Tied rank reflects only the number of distinct values preceding it + 1.
Primary Business Case	Scenarios where the literal volume of competitive rows must penalize down-stream rank.	Scenarios focused strictly on consecutive tiering or finding distinct “top N” groupings.
Max Rank Potential	The highest assigned rank value will always match the total row count of the set.	The highest assigned rank value will match only the total count of unique values in the set.

The Anatomy of the Query Syntax: Mapping the Window

To implement these functions correctly within your SQL scripts, you must understand the syntactic components that control the ranking boundaries. The structural anatomy of a ranking window function consists of three primary elements:

SQL

RANK() OVER (
    [PARTITION BY partition_expression]
    ORDER BY sort_expression [ASC | DESC]
)

1. The Core Function Calls

Both RANK() and DENSE_RANK() are invoked with completely empty parentheses. Unlike scalar transformation functions, you do not pass a column name directly into the function arguments. The column targeted for evaluation is specified exclusively inside the trailing window parameters.

2. The ORDER BY Clause (The Sorting Anchor)

The ORDER BY sub-clause inside the OVER parenthesis is the operational anchor of the function. It dictates the column attribute and direction (Ascending or Descending) that the database engine will use to sort the rows before calculating the numerical positions. If you sort via DESC, the highest numerical value receives rank 1; if you sort via ASC, the lowest value receives rank 1.

3. The PARTITION BY Clause (The Isolation Perimeter)

While the ORDER BY clause controls the sort direction, the PARTITION BY clause establishes the boundaries of the ranking calculation. It acts as an isolation perimeter, instructing the query engine to slice the large dataset into smaller independent buckets based on a specific attribute.

When a PARTITION BY clause is present, the ranking engine calculates ranks independently for each bucket. Every time the query processor encounters a new partition value, the internal ranking counter completely resets back to 1.

If you omit the PARTITION BY clause, the entire table is treated as a single massive partition, and the ranking sequence will calculate globally from the first row to the absolute end of the dataset.

Advanced Analytical Patterns: Selecting the Right Tool

Choosing between RANK and DENSE_RANK is not a matter of personal preference; it is dictated entirely by your specific underlying business logic and analytical intent. Let let us explore two common enterprise scenarios where selecting the wrong function would compromise data integrity.

Scenario A: Compensation and Bonus Distribution (Why RANK Matters)

Imagine you are building a sales commissions reporting framework for a logistics firm based in Houston, Texas. The executive team establishes a rule: “We want to distribute performance bonuses exclusively to the top 3 individual sales agents across the organization.”

Suppose the top agent sets the pace at rank 1. The next two agents achieve identical sales figures and tie for rank 2. Because of this tie, three distinct individuals have already filled the top positions of your bonus pool.

If you utilize DENSE_RANK, the next distinct agent in line would be assigned rank 3, qualifying them for a bonus payment. This expands your payout pool to four people, violating the explicit business mandate and causing an unbudgeted corporate expenditure.

By applying standard RANK, the fourth agent is correctly assigned rank 4, allowing your query to filter accurately for rows where RankValue <= 3, preserving the integrity of the business constraint.

Scenario B: Identifying the Distinct Top N Tiers (Why DENSE_RANK Wins)

Now consider an alternative analytical goal for a tech firm in Seattle, Washington. The HR VP asks for a report identifying every employee whose compensation falls within the top three distinct salary brackets in the company for equity mapping.

In large organizations, multiple employees frequently earn the exact same salary. If twenty engineers all share the absolute highest base salary in the firm, they will all tie for rank 1.

If you apply the standard RANK function here, the next distinct salary value down the line will be skipped all the way to rank 21. If your filtering logic looks for ranks less than or equal to 3, your report will completely exclude all subsequent salary tiers, failing to capture the second and third highest brackets.

By leveraging DENSE_RANK, those twenty engineers still occupy rank 1, but the next unique salary bracket smoothly transitions to rank 2, and the third highest bracket takes rank 3. This allows you to isolate the complete, multi-row population of the top three distinct financial tiers perfectly.

Conclusion:

Mastering the mechanics of SQL RANK vs DENSE_RANK is essential for a data professional. Recognizing that RANK evaluates positions based on total row counts—leaving gaps when encountering duplicates—while DENSE_RANK evaluates positions strictly by unique value tiers, allows you to align your code perfectly with complex corporate business logic.

You may also like the following articles:

Bijay Kumar Sahoo

After working for more than 15 years in the Software field, especially in Microsoft technologies, I have decided to share my expert knowledge of SQL Server. Check out all the SQL Server and related database tutorials I have shared here. Most of the readers are from countries like the United States of America, the United Kingdom, New Zealand, Australia, Canada, etc. I am also a Microsoft MVP. Check out more here.

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SQL Server Date Math

Bijay Kumar Sahoo — Tue, 17 Jun 2025 08:46:41 +0000

In this comprehensive article, I’ll walk you through everything you need to know about manipulating dates in SQL Server – from basic operations to advanced techniques. Let’s dive in.

SQL Server Date Math

Before we explore the specifics, it’s essential to understand why date manipulation is so critical in database applications:

Business Intelligence: Accurate period-over-period comparisons drive decision making
Compliance: Many industries (healthcare, finance, etc.) have strict time-based record-keeping requirements
Performance: Properly formatted date operations can dramatically improve query speed
Reporting: Almost every business report includes some form of date-based calculation

Check out SQL Server Date Data Types

Getting the Current Date and Time in SQL Server

Let’s start with the basics – retrieving the current date and time:

Example 1

We can execute the following query to return the date and time with SQL Server’s default precision.

-- Returns date and time with SQL Server's default precision
SELECT GETDATE() AS CurrentDateTime;

After executing the above query, I obtained the expected output, as shown in the screenshot below.

Example 2

We can execute the following query to return the date and time with higher precision.

SELECT SYSDATETIME() AS CurrentDateTimeHighPrecision;

After executing the above query, I obtained the expected output, as shown in the screenshot below.

Example 3

We can execute the following query to return just the current date.

SELECT CONVERT(date, GETDATE()) AS CurrentDate;

Below is the expected output after executing the above query.

Example 4

We can execute the following query to return just the current time.

SELECT CONVERT(time, GETDATE()) AS CurrentTime;

Below is the expected result after executing the above query.

Essential Date Math Operations in SQL Server

Now let’s explore the fundamental date math operations you’ll use regularly.

Adding and Subtracting Time Periods with DATEADD

The DATEADD Function is your primary function for adding or subtracting time intervals:

Example 1

Let us execute the following query to add 7 days to the current date.

SELECT DATEADD(day, 7, GETDATE()) AS OneWeekFromNow;

I got the expected output after executing the above query.

Example 2

We can execute the following query to subtract 3 months from the current date.

SELECT DATEADD(month, -3, GETDATE()) AS ThreeMonthsAgo;

Below is the expected result after executing the above query.

Example 3

We can execute the following query to add 4 hours to the current time.

SELECT DATEADD(hour, 4, GETDATE()) AS FourHoursLater;

I obtained the expected output after executing the query as shown in the screenshot below.

Example 4

We can execute the following query to add 30 seconds.

SELECT DATEADD(second, 30, GETDATE()) AS ThirtySecondsLater;

Below is the expected result after executing the above query.

DATEADD accepts the following interval types:

year, yyyy, yy
quarter, qq, q
month, mm, m
dayofyear, dy, y
day, dd, d
week, ww, wk
hour, hh
minute, mi, n
second, ss, s
millisecond, ms
microsecond, mcs
nanosecond, ns

Calculating Time Differences with DATEDIFF

The DATEDIFF Function calculates the difference between two dates:

Example 1

Let us execute the following query to find the days between two dates.

SELECT DATEDIFF(day, '2025-01-01', '2025-12-31') AS DaysInYear;

Below is the expected result after executing the above query.

Example 2

Let us execute the following query to find the months between two dates.

SELECT DATEDIFF(month, '2024-03-15', GETDATE()) AS MonthsSinceDate;

Below is the expected result after executing the above query.

Example 3

Let us execute the following query to find the minutes between two times.

SELECT DATEDIFF(minute, '2025-05-04 09:30:00', '2025-05-04 11:45:00') AS MinutesDifference;

Below is the expected result after executing the above query.

Extracting Date Parts with DATEPART

To extract specific components from a date with DATEPART function:

Example 1

We can execute the following query to get the current month number (1-12).

SELECT DATEPART(month, GETDATE()) AS CurrentMonth;

After executing the above query, I got the expected output as per the screenshot below.

Example 2

We can execute the query below to retrieve the day of the week (1 = Sunday, 2 = Monday, etc.).

SELECT DATEPART(weekday, GETDATE()) AS DayOfWeek;

I got the expected output after executing the above query.

Example 3

We can execute the below query to get the hour from a datetime.

SELECT DATEPART(hour, GETDATE()) AS CurrentHour;

I got the expected output after executing the above query as per the below screenshot.

Performance Considerations

Below are the performance tips

Avoid functions on indexed columns– Bad (can’t use index) WHERE YEAR(OrderDate) = 2023 — Good (can use index) WHERE OrderDate >= ‘2023-01-01’ AND OrderDate < ‘2024-01-01’

2. Use appropriate data types– More efficient when you only need a date OrderDate date NOT NULL.

Conclusion

Date manipulation is so critical in database applications that you have to know as a database developer working with SQL Server. You can use the information mentioned in this article.

You may also like the following articles.

Bijay Kumar Sahoo

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SQL Server GROUP BY Date

Bijay Kumar Sahoo — Mon, 14 Apr 2025 08:28:23 +0000

Recently, I received a requirement for aggregating data by date. In this comprehensive article, I’ll walk you through various techniques for effectively using SQL Server’s GROUP BY clause with date values and provide multiple examples.

SQL Server GROUP BY Date

Dates in SQL Server contain date and time components, meaning when you group by a datetime column, SQL Server groups records by the exact timestamp.

Let us discuss all the possible methods of how to group by date in SQL Server.

Method 1: Using CAST and CONVERT Functions

The most straightforward approach to grouping by date (ignoring time) is to use SQL Server’s CAST or CONVERT functions.

Using CAST Function

SELECT CAST(Sale_Date AS DATE) AS SaleDay, 
       SUM(sale_amount) AS TotalSales
FROM Sales
GROUP BY CAST(Sale_Date AS DATE)
ORDER BY SaleDay

After executing the above query, I got the expected output, which is shown in the screenshot below.

Using CONVERT Function

SELECT CONVERT(DATE, Sale_Date) AS SaleDay, 
       SUM(Sale_Amount) AS TotalSales
FROM Sales
GROUP BY CONVERT(DATE, Sale_Date)
ORDER BY SaleDay

After executing the above query, I got the expected output, as shown in the below screenshot.

Method 2: Grouping by Month, Quarter, and Year

SQL Server offers several approaches in this case.

Grouping by Month

Here, we can use the DATEPART() using this query.

SELECT DATEPART(YEAR, Sale_Date) AS Year,
       DATEPART(MONTH, Sale_Date) AS Month,
       SUM(sale_amount) AS MonthlySales
FROM Sales
GROUP BY DATEPART(YEAR, Sale_Date), DATEPART(MONTH, Sale_Date)
ORDER BY Year, Month

After executing the above query, I got the expected output as shown in the screenshot below.

We can also use the Date() for this purpose.

SELECT YEAR(Sale_Date) AS Year,
       MONTH(Sale_Date) AS Month,
       SUM(Sale_Amount) AS MonthlySales
FROM SalesTransactions
GROUP BY YEAR(Sale_Date), MONTH(Sale_Date)
ORDER BY Year, Month

After executing the above query, I got the expected output, as shown in the screenshot below.

Grouping by Quarter

We can also group by quarter using the DATEPART function in the query below.

SELECT DATEPART(YEAR, Sale_Date) AS Year,
       DATEPART(QUARTER, Sale_Date) AS Quarter,
       SUM(sale_amount) AS QuarterlySales
FROM Sales
GROUP BY DATEPART(YEAR, Sale_Date), DATEPART(QUARTER, Sale_Date)
ORDER BY Year, Quarter

After executing the above query, I got the expected output, as shown in the screenshot below.

Grouping by Year

We can also group by year using the query below.

SELECT YEAR(Sale_Date) AS Year,
       SUM(sale_amount) AS AnnualSales
FROM Sales
GROUP BY YEAR(Sale_Date)
ORDER BY Year

After executing the above query, I got the expected output, as shown in the screenshot below.

Method 3: Using EOMONTH

Using the query below, we can also use the EOMONTH function (available in SQL Server 2012 and later).

SELECT EOMONTH(Sale_Date) AS MonthEndDate,
       SUM(sale_Amount) AS MonthlySales
FROM Sales
GROUP BY EOMONTH(Sale_Date)
ORDER BY MonthEndDate

After executing the above query, I got the expected output, as shown in the screenshot below.

Method 4: Date Groupings with DATEADD and DATEDIFF

We often use the combination of DATEADD and DATEDIFF functions.

Grouping by Week (Starting Sunday)

SELECT DATEADD(DAY, 
       DATEDIFF(DAY, 0, Sale_Date)/7*7, 0) AS WeekStartDate,
       SUM(sale_Amount) AS WeeklySales
FROM Sales
GROUP BY DATEADD(DAY, DATEDIFF(DAY, 0, Sale_Date)/7*7, 0)
ORDER BY WeekStartDate

After executing the above query, I got the expected output, as shown in the screenshot below.

Method 5: Using the FORMAT Function

SQL Server 2012 introduced the FORMAT function, which provides great flexibility for date formatting.

SELECT FORMAT(Sale_Date, 'yyyy-MM (MMMM)') AS MonthGroup,
       SUM(sale_amount) AS MonthlySales
FROM Sales
GROUP BY FORMAT(Sale_Date, 'yyyy-MM (MMMM)')
ORDER BY MIN(Sale_Date)

After executing the above query, I got the expected output, as shown in the screenshot below.

Best Practices

Below are some best practices while working with SQL server date grouping.

Be consistent with your date grouping approach throughout your application
Consider performance implications for large datasets
Use appropriate data types – DATE for date-only values, DATETIME2 for higher precision needs
Create helper functions for complex date logic to ensure consistency
Test with edge cases like leap years, daylight saving time changes, and month boundaries

Video Tutorial

Conclusion

By understanding these various methods, you can choose the right solution for any date grouping requirement. Remember that the best approach depends on your specific requirements, data volume, and performance needs.

SQL Server MAX Date

Bijay Kumar Sahoo — Thu, 03 Apr 2025 12:12:20 +0000

In this article, I’ll explain various methods for finding and working with the max() for date in SQL Server with multiple examples.

SQL Server MAX Date

The foundation of finding the most recent date in SQL Server is the MAX function, which returns the highest value in a selected column. When applied to date columns, it identifies the most recent date in your dataset.

Syntax

SELECT MAX(date_column) FROM table_name;

Example 1: Basic One

For example, if we have an orders table and want to find the most recent order date, we can execute the below query.

SELECT MAX(order_date) AS "Most Recent Order" 
FROM orders;

After executing the above query, I got the expected output, as shown in the screenshot below.

Example 2: Using Subquery with GROUP BY

The query below first identifies the maximum date for each order and then returns to the original table to get all columns for those records.

SELECT o.order_id, o.order_date, o.order_name
FROM orders o
INNER JOIN (
    SELECT order_id, MAX(order_date) as max_date
    FROM orders
    GROUP BY order_id
) latest ON o.order_id = latest.order_id AND o.order_date = latest.max_date;

After executing the above query, I got the expected output, as shown in the below screenshot.

Example 3: Using ROW_NUMBER() Function

The ROW_NUMBER() function often provides better performance for complex queries. This method assigns a row number to each record within its customer partition, ordered by date descending, then filters for only the first row in each group.

WITH RankedOrders AS (
    SELECT 
        order_id, 
        order_date, 
        order_name,
        ROW_NUMBER() OVER(PARTITION BY order_id ORDER BY order_date DESC) as rn
    FROM Orders
)
SELECT 
    order_id, 
    order_date, 
    order_name 
FROM RankedOrders
WHERE rn = 1;

After executing the above query, I got the expected output, as shown in the screenshot below.

Example 4: Finding Records with the Overall Latest Date

You can execute the query below if you need to find all records that occurred on the most recent date in your entire dataset. This will return all orders placed on the latest date in the system.

SELECT order_id, order_name, order_date
FROM orders
WHERE order_date = (SELECT MAX(order_date) FROM orders);

After executing the above query, I got the expected output, which is shown in the screenshot below.

Optimizing MAX Date Queries for Better Performance

Finding maximum dates can become a performance bottleneck, especially with large datasets. Here are some optimization techniques:

1. Proper Indexing

Creating an index on your date column is critical for performance optimization. The query below can help you do that.

CREATE INDEX idx_order ON orders(order_date);

After executing the above query, I got the expected output shown in the screenshot below.

Consider a composite index for queries frequently finding the maximum date within groups. The query below can be used.

CREATE INDEX idx_order_date ON orders(order_id, order_date DESC);

After executing the above query, I got the expected output, as shown in the below screenshot.

2. Using Filtered Indexes for Recent Data

If your application mostly queries recent dates, consider a filtered index:

CREATE INDEX idx_recent_orders ON orders(order_date)
WHERE order_date > '2024-01-01';

After executing the above query, I got the expected output, as shown in the below screenshot.

Handling NULL Date Values

MAX() will ignore NULL values, which can lead to unexpected results. However, you can explicitly use the query below to handle the NULL date.

SELECT order_id, 
       MAX(COALESCE(order_date, '1900-01-01')) as latest_order
FROM orders
GROUP BY order_id;

After executing the above query, I got the expected output, as shown in the below screenshot.

Video Tutorial

Conclusion

Finding max dates in SQL Server is essential for developers. This article provides the best output by using the above examples. For better performance, try creating indexes as mentioned above.

You may also like the following articles below

Bijay Kumar Sahoo

sqlserverguides.com

SQL Server Get Current Date

Bijay Kumar Sahoo — Tue, 01 Apr 2025 11:01:58 +0000

As a senior database developer working with SQL Server, I’ve found that retrieving the current date and time is one of your most fundamental operations. In this comprehensive article, I’ll walk you through various methods to get the current date in SQL Server and share best practices based on real-world examples.

SQL Server Get Current Date

SQL Server provides several built-in functions to retrieve the current date and time. Each serves a specific purpose and has unique characteristics that make it suitable for different scenarios.

Using GETDATE()

The most commonly used function to retrieve the current date and time in SQL Server is GETDATE(). This function returns the current database system timestamp as a datetime value.

SELECT GETDATE() AS CurrentDateTime;

After executing the above query, I got the expected output, as shown in the below screenshot.

Using CURRENT_TIMESTAMP

If you’re working in an environment where code portability is essential, CURRENT_TIMESTAMP is your best option as it follows the ANSI SQL standard:

SELECT CURRENT_TIMESTAMP AS CurrentDateTime;

After executing the above query, I got the expected output, which is shown in the screenshot below.

Getting Just the Date (Without Time)

Sometimes, you only need the date portion without the time. Here are methods I’ve successfully implemented for my clients:

Method 1: Using CONVERT ()

To get the current date, we can use the query below with CONVERT() and GETDATE().

SELECT CONVERT(date, GETDATE()) AS CurrentDate;

After executing the above query, I got the expected output, as shown in the screenshot below.

Method 2: Using CAST ()

We can also use the query below with CAST() and GETDATE() to get the current date.

SELECT CAST(GETDATE() AS date) AS CurrentDate;

After executing the above query, I got the expected output, as shown in the screenshot below.

Method 3: Using DATEADD and DATEDIFF

We can use the DATEADD () and DATEDIFF (). This method effectively truncates the time portion and only provides the current date. We can use the query below for this purpose.

SELECT DATEADD(dd, DATEDIFF(dd, 0, GETDATE()), 0) AS CurrentDate;

After executing the above query, I got the expected output, as shown in the below screenshot.

Formatting Dates

These methods are effortless when presenting dates to users or storing them in specific formats.

Common Date Formats

Format	Code	Output
MM/DD/YYYY	101	08/15/2023
YYYY-MM-DD	120	2023-08-15
Mon DD YYYY	107	Aug 15 2023
YYYY/MM/DD	111	2023/08/15

Example

SELECT 
    CONVERT(varchar, GETDATE(), 101) AS USDateFormat,
    CONVERT(varchar, GETDATE(), 120) AS ISODateFormat,
    CONVERT(varchar, GETDATE(), 107) AS MonthDayYearFormat;

After executing the above command, I got the expected output, as shown in the below screenshot.

Best Practices for Working with Dates in SQL Server

Based on my experience optimizing database performance, here are my recommendations:

Use appropriate data types: Use date When you only need the date, saving storage space and improving query performance
Be mindful of indexes: Avoid functions on indexed date columns in WHERE clauses
Consider time zones: Always store dates in UTC and convert to local time zones at the application level.

Video Tutorial

Conclusion

Using date and time functions will significantly enhance your database development capabilities. From the standard GETDATE() to more specialized functions like SYSDATETIMEOFFSET(), SQL Server provides you with this option to handle this.