Creating a database from scratch: Part 1 - Understanding the basics

• A database is an essential component of any modern application, providing a repository for storing and retrieving large amounts of information.
• Building a database can seem daunting, but it can be straightforward with the right tools and techniques.
• Structured Query Language (SQL) is the foundation of most relational databases.

A database is an organized collection of structured data stored and accessed electronically. It is made so that large amounts of data can be quickly retrieved, added, or deleted.

Databases are used for a wide range of services and applications, like storing data, managing data, and analyzing data.

While small databases can be hosted on a file system, large databases are housed on computer clusters or in the cloud.

You may be familiar with some of it, but if you're new to the database, don't worry; here's some basic information to get you started.

Main components of database

The main components of a database are:

• Tables: A table is a collection of related data organized into rows and columns. Tables are used to store data in a relational database. If you've ever used spreadsheet applications like Microsoft Excel, you should have a basic understanding of what these are.
• Fields: Fields are the individual pieces of data within a table. Each field contains a specific data type, such as a text string, numeric value, or date. These are equivalent to "cells" in a spreadsheet.
• Records: Records are individual rows in a table that contain related data. Each record corresponds to a single item or instance of data, such as a specific customer, product, or transaction.
• Primary Key: A primary key is a unique identifier for each record in a table. It is used to enforce referential integrity and to ensure that each record can be uniquely identified and retrieved. It is, in other words, a record's unique ID card; it tells the database, "hey, here I am!"
• Foreign Key: A foreign key is a field in one table that refers to the primary key of another table. Foreign keys are used to establish relationships between tables and to enforce referential integrity. This is one of the most potent elements of a database, and you'll come to love them!
• Queries: A query is a request for data from a database. Queries are used to search and retrieve specific data from a database.
• Indexes: An index is a database structure that helps to speed up query performance by allowing the database to locate specific records quickly.
• Views: A view is a virtual table based on a query's result. Views provide a way to present a subset of data from a database in a specific format.

Don't worry if you are not familiar with most, if not all, of these terms, as you'll quickly get to grips with them once you start building your own database.

How to create your own database?

Building a database requires a little thought and unless experienced, a lot of trial and error. You'll need to factor in a few key issues before you begin but try not to get lost in the details at this stage.

Generally speaking, when considering building your database, you'll want to consider the following points: -

• Determine the purpose and requirements of the database: what kind of data will be stored, the relationships between the data, who will use the database, and what kind of queries will be performed on the data.
• Choose a database management system (DBMS) that fits your requirements. Examples of DBMS include MySQL, PostgreSQL, Microsoft SQL Server, and Oracle. Some are better than others for specific purposes (whether you'll be using on a local computer or plan on having thousands or more users, etc.), and we'll discuss this in a little more detail later.
• Design the database schema: create a visual representation of the database structure, including tables, columns, data types, and relationships between tables.
• Implement the database schema: create tables and columns in the chosen DBMS, and specify constraints such as primary keys and foreign keys.
• Populate the database with data: add data to the tables and verify that it meets the constraints.
• Test the database: perform queries on the data to ensure that it can be retrieved as required.
• Maintain the database: regularly back up the data, monitor performance, and make updates as needed to ensure that the database continues to meet the needs of its users.

In the vast majority of cases, the above simple checklist will suffice, but for large deployments (like an app that will have millions of users, say), there will be other issues to deal with. However, such large implementations are beyond the scope of this introductory overview.

So, once you've made the big decision to build a database, one of the most important decisions you'll need to make is which DBMS to choose.

What database management system should you choose?

The best DBMS for building a database depends on several factors, including:

• Purpose of the database: different DBMS are optimized for different purposes. For example, some DBMSs are designed for transaction processing, while others are designed for data warehousing.
• The scale of the database: the size of the database, the number of users, and the amount of data that will be stored all impact the choice of DBMS.
• Performance requirements: the response time and throughput required for queries and transactions will also affect the choice of DBMS.
• Cost: different DBMS have different licensing fees and hardware requirements.

Based on these considerations, some popular DBMS for database development include:

• MySQL: a widely used open-source relational database management system.
• PostgreSQL: a powerful and open-source object-relational database management system.
• Microsoft SQL Server: a popular commercial relational database management system.
• Oracle Database: a powerful and widely used commercial relational database management system.
• Microsoft Access: an older DBMS and prone to something called "bloating," but it is great for beginners. The user interface is second to none for building your relational database, forms, and queries.

• MongoDB: a document-oriented NoSQL database management system known for its scalability and ease of use.

The best choice will depend on the size and complexity of your database, the type of data you need to store, performance requirements, and budget. Evaluating a few different options is recommended, and choosing the one best fits your needs.

What are some common tips for building a database?

So, you've made it this far. Not too daunting, is it? But, before we get deeper into more specifics (like making an actual database using any of the DBMSs mentioned above, here are some key takeaways you should always keep in the front of your mind.

1. You can "sketch out" your database using spreadsheets first

Since databases are fancy collections of connected tables, you may want to plan your first database using Excel. This will focus your mind on the data you wish to and types and helps you find ways to reduce or eliminate data replication.

Take cell dropdown lists, for example. That can be a separate table in your database that connects (i.e., is relational) to a central data table.

It can also save you a ton of time if you already have some datasets you want to convert into spreadsheet form. In most cases, you can import the spreadsheet as a new table in your database!

2. SQL is at the heart of most databases

Structured Query Language (SQL) is the foundation of most relational databases. So, consider this a "must learn" since it offers a uniform interface to relational databases like Oracle, SQL Server, Microsoft Access, and others.

SQL isn't that tricky to pick up, and there are plenty of free and paid-for learning resources online.

3. Primary keys are your friend but choose wisely

Choosing a primary key is one of the most important decisions when designing a new database. You must ensure that the selected key is unique, which is the main restriction.

A shared attribute is a wrong choice for a primary key if one value attribute can appear in two records. Additionally, it would be best to avoid private information like Social Security numbers and other delicate values as a primary key.

4. Learn the difference between null, empty string, and zero values

Although NULL is a unique value in databases, newcomers frequently misunderstand it.

Consider a NULL value to mean "unknown" whenever you encounter one. For instance, a NULL quantity need not always be zero. A text field with a NULL value indicates that the value is unknown rather than inappropriate.

It is, in effect, a placeholder rather than a piece of data.

And that is your lot for today.

By following the steps outlined above, you should have a solid foundational understanding of the process and be able to design and build a database that meets your specific needs. Remember to take the time to plan your database structure, choose the right technology, and test your database thoroughly before deployment.

With these best practices in mind, you can build a database that is reliable, scalable, and optimized for performance. Whether you're a seasoned developer or just starting, the knowledge and skills you've gained from this article will serve as a valuable foundation for future database development projects.

In the next episode of this series, we'll guide you through building one using one of the most common DBMSs, MySQL.