When working with SQL Server, one of the most common operations is manipulating data using the INSERT statement. Alongside SELECT, UPDATE, and DELETE, the INSERT statement is a fundamental part of data manipulation in SQL. In this article, we will delve into the concept of Query Plan Analysis and explore the various use cases of the VALUES statement in SQL Server.

In SQL Server 2005, the basic syntax of the INSERT statement involved using the VALUES keyword only for inserting records. However, with the release of SQL Server 2008, the syntax was expanded, allowing for multiline VALUES statements for more versatile usage. In this article, we will focus on several possible cases of using the VALUES statement and analyze the query plan for each example using the built-in Profiler of dbForge Studio for SQL Server.

Let’s consider a scenario where we have a table called “Players” with columns for PlayerID, GoldBadge, SilverBadge, and BronzeBadge. Our goal is to find the maximum number of medals (regardless of their value) for each player. To accomplish this, we need to convert the columns into rows and then apply the MAX aggregation function.

One common approach, especially among beginners, is to read the data multiple times from the table. However, starting from SQL Server 2005, the UNPIVOT operator is generally used to convert columns into rows, resulting in more efficient data retrieval. By using the UNPIVOT operator, we can read the data from the table only once, significantly improving performance.

Another bottleneck in our query is the Sort operation, which is the most resource-consuming operation. To avoid row sorting, we can utilize the VALUES statement. By using the VALUES statement, we can eliminate the need for sorting and improve query performance.

In addition to converting columns into rows, the VALUES statement can also be used for formatting row-wise data output in a grouped table. Instead of reading the data multiple times using UNION ALL with sorting, the VALUES statement allows for a more sophisticated query that achieves the desired result.

It’s important to note that the VALUES statement is not a full substitute for the UNPIVOT statement or a solution for all scenarios. The effectiveness of the VALUES statement depends on the query plan, and analyzing it with the help of Profiler in dbForge Studio for SQL Server allows us to identify potential bottlenecks in query performance.

While we are discussing SQL Server tools, it’s worth mentioning the Database Diagram tool from dbForge. This tool allows us to visualize the database structure for further analysis and helps in creating and editing database objects on a diagram.

By understanding the various use cases of the VALUES statement and analyzing the query plan, we can optimize our SQL code and improve the performance of our SQL Server queries.