Database normalization is a process used to organize a database into tables and columns. The idea is that a table should be about a specific topic and that and only supporting topics included. Normalization is a systematic approach of decomposing tables to eliminate data redundancy.
A database View is nothing else than a stored query! When you create a database view (CREATE VIEW), the database engine stores the input query and give him a specified name. When you query the view, the database engine take the stored definition of the query and execute it with added statements by you (e.g. ORDER BY, WHERE, etc.) and execute it.
A database key provides the possibility to identify, access and update information in a database table. A key is a single field (column) or combination of multiple fields. Its purpose is to access or retrieve data rows from table according to the requirement. The keys are defined in tables to access or sequence the stored data quickly and smoothly. They are also used to create links between different tables.
Alias is a shorten name for a table (sometime even a function) that can be used in queries.
When talking about values in database world there are three possible states. The three states are: there is a value, there is not a value (empty) and the value is NULL (unknown). Let's find out more about the NULL value.
Let’s find out what is a JOIN and how to use it. The main difference between JOIN and UNION operator is that union combines results vertically, while the JOIN combines result's horizontally. There are different types of JOIN-s depending on the business need and we will discuss about them. Since the databases should be normalized it is essential to use joins to get details for some records.
Let’s find out what is a UNION and what’s the difference between the UNION and the UNION ALL operators. The main difference between UNION and JOIN operator is that union combines results vertically. In simple words, the UNION operator returns results from two or more queries in one result set.
If you want to check for data existence in a table (e.g. if there are invoices on a concrete date) you could use COUNT(*) or the EXISTS statement. I found various theories on the internet and even in some SQL books what is the best approach, so I decided to test this by myself (spoiler alert: the books are on the side of using EXISTS).
Why you should use constraints on your tables? Except the fact that you should use constraints to check your data and the integrity of them (e.g. only allow inserting of numeric value between 1 and 5 for storing vote value) you could use them also for better query executions and get some performance boost. Let’s find how.
In short words, hashing is a process of generating a value or values from a string of text using a mathematical function. Let's see the usage of the MS SQL function HASHBYTES witch purpose is to hash values. MS SQL function HASHBYTES was introduced in MS SQL version 2005 supporting MD2, MD4, MD5, SHA, SHA1 hashing algorithms. From MS SQL server version 2012 additionally the SHA2_256, SHA2_512 algorithms were introduced. In this article we will discuss about hashing, what's new from SQL 2016 and see some usage examples.
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