SQL Triggers are another powerful database object we have at our disposal. In previous articles, we’ve covered user-defined functions, user-defined procedures, and SQL Views. Today we’ll talk about SQL triggers and how to use them to achieve the desired behavior.

SQL Server provides us with several aggregate functions that can be used to perform different types of calculations on a set of values, and return a single value that summarized the input data set. These SQL Server aggregate functions include AVG(), COUNT(), SUM(), MIN() and MAX().

This article explores the SQL Server TOP clause using various examples, along the way, we will also run through performance optimization while using the TOP clause in SQL Server.

SQL views are another powerful database object we have at our disposal. In the previous two articles of this series, we’ve talked about user-defined functions and user-defined procedures and showed simple examples of how to use them. Today, we’ll do the same for the SQL views.

This article explains the usage of SQL Format function and performance comparison with SQL CONVERT.

This article explores the SQL Server session context function, SESSION_CONTEXT() and performs its comparison with the function, CONTEXT_INFO().

This article walks through different versions of the T-SQL IF EXISTS statement for the SQL database using various examples.

You can create several user-defined objects in a database. One of these is definitely user-defined functions. When used as intended, they are a very powerful tool in databases. In today’s article, we’ll see how to create, change and remove them from the database, as well as how to use them. So, let’s dive into the matter.

In this article, we will learn the SQL CROSS JOIN concept and support our learnings with straightforward examples, which are explained with illustrations.

The set theory is very important in order to understand data and databases. While you could live without it and still be a good SQL developer, understanding it will surely help a lot. So, let’s dive into the matter.

This article explores the uses of the SET PARSEONLY SQL command for SQL Server queries.

This article gives you an insight into the SQL Truncate and SQL Delete commands behavior.

What are SQL data types, why do we need them, and how to use them? Today, we’ll try to answer these questions by giving an overview of some most common data types used in SQL Server.

SQL AS keyword is used to give an alias to table or column names in the queries. In this way, we can increase the readability and understandability of the query and column headings in the result set.

The best way how to explain what the INFORMATION_SCHEMA database is would be – “This is the database about databases. It’s used to store details of other databases on the server”. What does that mean, how we can use it, and what we can do with this data is the topic of today’s article.

In my career, I’ve heard many times, things like “How to write a complex SELECT query?”, “Where to start from?” or “This query looks so complex. How you’ve learned to write such complex queries?”. While I would like to think of myself as of a brilliant mind or genius or add something like “query magician” to my social network profiles, well, writing complex SQL wouldn’t be the only thing required to do that. Therefore, in this article, I’ll try to cover the “magic” behind writing complex SELECT statements.

Today, data is the basis of any business. The world of enterprise computing is the epitome of data-driven businesses. The importance of structured storage of data is unquestionably in the focus. And at this time, with the computing model quickly shifting towards the cloud, and storage costs falling rapidly, enterprises are leveraging data more and more to tune their businesses.

SQL has many cool features and aggregate functions are definitely one of these features, actually functions. While they are not specific to SQL, they are used often. They are part of the SELECT statement, and this allows us to have all benefits of SELECT (joining tables, filtering only rows and columns we need), combined with the power of these functions.