how database works

What is a database, anyway? It’s not just a collection of tables, right? A database has something to do with storage, right? Well, sort of.

At its heart, a database is nothing more than a collection of data that’s organized in such a way that we can query it efficiently and access the data we need quickly.
That sounds pretty abstract and technical until you actually start looking into how databases are structured. Let’s take a look at what makes up the physical structure of a database and how DDL (Data Definition Language) helps us manage our schema.

What is a database?

The physical structure of a database is actually pretty simple, but the DDL (Data Definition Language) helps provide some structure to how different parts of the database interact with each other.

database Server
A database is nothing more than a collection of data that’s organized in such a way that we can query it efficiently and access the data we need quickly. The physical layout of the database itself is quite easy—it’s just a series of files on a hard drive or even across multiple hard drives. But what makes up all that data?

Ultimately, there are three major pieces that make up any database: tables, columns, and constraints.
Tables are usually made up of records or rows and fields or columns. Columns are where individual values for an individual row appear—and these columns can be defined as either primary or secondary.

Primary means they’re only allowed to have one value during insertion; secondary means they can have many values but they only appear once per row when inserted into the table. Constraints define rules for matches on values within columns—for example, you might want to allow certain values in only certain rows of your table while prohibiting others entirely.

What is DDL?

Data Definition Language (DDL) is a set of rules that tells the database how to store and organize data. Let’s break down what this means with an example.
Let’s say we have a database that stores all of our customer records. With this database, we have customers linked to their orders by their order ID number, which is also called the primary key. We also have customers linked to their order information like the products they bought or their shipping address.
To manage these relationships in our schema, we use DDL to create a table for each type of relationship. For example, we could create a table for orders and another table for products so that each record in one of these tables has at least one foreign key field pointing back to a record in the other table.

This way, every time someone makes a new order, it will automatically go into the orders table, and all products included in that order will be stored in the product table.

How SQL works with a database

The physical structure of a database is made up of tables that are laid out logically. So, how do you manage that structure and what’s the best way to query it? Well, that’s where SQL comes in. SQL (Structured Query Language) is used to create and manage the database, in addition to querying the data within it.

Not only does SQL help us create databases and organize them logically, but it also helps us find what we need when we need it.
When you want to find a specific table or column in your database, you can easily use SQL to help with this process. Then, once you have found your piece of data, you can see all or part of its associated records with a simple SELECT statement.

SQL and the relational model

SQL (Structured Query Language) is the language we use to communicate with databases. Sometimes referred to as Transact-SQL, it’s a de facto standard for communicating with relational databases. SQL is a language that’s simple enough to be used by non-programmers and powerful enough to manage our data on its own.

It supports Boolean logic operations, joins, transactions, and more. The relational model is the conceptual model of how data should be organized in a database. In this model, we organize data into tables that relate to each other through relationships. The physical structure of the data isn’t important; what matters is the way in which we’re organizing it.
The SQL schema of a database contains all the information necessary to define how our tables are laid out and what they contain as well as what their relationships are. This schema tells us which columns belong to which tables and defines how those columns relate to one another.

For example, let’s say you have an article table and a user table that relates back and forth from one another through a foreign key relationship known as ‘FK_user_id’. These two tables would then share common columns such as ‘title’ or ‘body’.
A DDL file helps us manage our schema so that it can be shared across multiple databases or even different platforms or languages. A DDL file is nothing more than an XML file containing all the definitions for your schema in relation to your database’s physical structure.

The difference between relational and non-relational databases

First, let’s talk about the difference between relational and non-relational databases.
A relational database is made up of tables that are related to one another by a column of data. This means that there’s a strong match between the way the data is stored in a table and its relation to other tables in the database. A non-relational database doesn’t require these strict associations like with relational ones.

Non-relational databases can include many different types of structures as long as they’re all organized into a schema (schema being simply defined as “a set of rules for defining, organizing, and managing information in a database”). This means that each field within this structure has certain restrictions on how it can be used (for example, only dates or numbers).

Relational Database Management Systems (RDBMSs)

The physical structure of a database is made up of rows and columns. These are the pieces that make up the data, and each piece is known as a table. If you take a look at your favorite database management system (DBMS), you’ll see that it has all these tables with different fields in them, which are the pieces of information about what’s stored in the database. Rows are where we have data; columns, on the other hand, hold information about what’s in those rows. Each field stores data about something specific to that table: for example, one column might store names, another might store numbers, and yet another might store dates. This type of organization is called relational—every table contains similar types of information that relate to one another.

Object-Oriented Database Management Systems (OODBMSs)

A database is a collection of data that needs to be stored and managed in such a way that we can query and access it efficiently. A database management system (DBMS) is software that’s responsible for the management of this data and securing it from unauthorized access.

Object-oriented Database Management Systems (OODBMSs) are designed with an object-oriented programming language, which means they can be created with easier development tools like frameworks. OODBMSs use more advanced language constructs, like classes, objects, inheritance, polymorphism, and encapsulation to create a well-defined structure for different types of data. For example:

A Database schema manages information about your company’s employees.
Each employee has a unique identifier that you can refer to later on when you’re querying databases.
The last name of an employee is stored in one table, which stores the first name of their spouse in another table.
An employee_id class is used as the user object type in every table to ensure that each row is saved properly; this also provides secondary keys for faster retrieval of each row from the database.

The primary key of the Table Data entry would be the employee_id class. It also includes columns for marital status (single/married), given name, and surname.


In order to get the best out of your database, it is important to know how it works. To put it simply, a database is a collection of data.

There are two types of databases in existence: relational and non-relational. A relational database works based on the relational model while a non-relational database works on objects. It is also important to note that an RDBMS is a type of database software while an ODBMS is not.



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