Author | Emily Williamson
Translator | Sun Wei, Editor-in-Chief | Tu Min
Listing | CSDN (ID: CSDNnews)
The following is the translation:
Databases are the core elements of applications and computers, and are responsible for storing all the important data needed to run software applications. In order to ensure the normal operation of the application, there is always one or more databases running silently. We can regard the database as an information warehouse, store a large amount of relevant information in a structured way, and classify it reasonably for easy search and use.
Therefore, database design has become an important part of software development, and it is very important for developers to design an efficient database. So why does database design matter, and what are the criteria for "good"? This article will do the introduction.
Why is database design important?
Take, for example, our online shop site for ordering shirts. These days, the process of ordering a shirt from a website may seem simple, but involves a lot of information exchange. For example: when you browse the web for the first time, the system will show you a series of information, including product categories, all available products, corresponding prices, available sizes, colors, and other relevant information. The website retrieves the data from the database where the data is stored, and when the user selects the desired item and proceeds to make a purchase, the website asks for personal details, shipping address, payment details, and confirms the order. New data currently generated during this process such as user details, order details, purchases and payments are all added and updated in the same database.
Database design is important because it is critical to building software applications that are scalable and able to run under high workloads. Designing a database First of all, the choice of database software is critical. There are hundreds of database software available to build applications today, we can choose from some of the best free database software, and then it's time to design a database that meets our requirements. Listed below are 10 best database design practices.
10 Best Practices for Database Design
Take everyone's opinions into account
To design a good database, the viewpoints of all stakeholders must be considered. Before building a database, gather information about their expectations for the database and their proficiency in operating the database. This gives an idea of the level of technology the database should be in, and whether users should be trained on the capabilities of the database.
Choose the type of database that meets your needs
There are many types of databases, and choosing the right type is the key to database design. We can categorize databases in two ways. One is the database-based query language used to define and manipulate data. Databases using SQL are the most common type of structured data. However, due to their scalability, flexibility, and speed, NoSQL databases are more suitable for machine learning, network analysis, and Internet of Things (IoT) use.
The second classification is based on data models. There are four types of such classification: relational database, hierarchical database, network database and object-oriented database.
Researching the different types of databases and making a choice for the application needs is a necessary initial step.
Define and label tables and columns in a consistent manner
When defining data items and labeling tables and columns, it is important to follow the principles of consistency to help us better understand the data. One of the best practices for naming tables and columns is to use simple names to define the data they contain. For example: just label the column containing the user name as "CustomerName" ("username").
Plural names (such as CustomerNames), abbreviations (such as CN), and spaces in names (such as Customer Name) should be avoided. If you stick to these rules, it will be easier for future users to use the database.
Normalization is the key
Database normalization refers to organizing all the information in the database to avoid data duplication and redundancy. In a nutshell, normalization is the breaking up of data into several smaller, related tables, rather than all in one large table.
Normalizing data is good database design practice and helps improve efficiency. But make sure you don't over-normalize, or you'll spread the data across too many small tables, creating a mess.
Documentation of database design is important
In fact, documentation is not everyone's favorite because it's so annoying. But remember, documentation is critical to good database design to keep track of all the little details. The database design should be accompanied by instructions, ER diagrams, stored procedures and all other relevant information. Documentation should also provide sufficient information for programmers and end users to understand and use.
Privacy is a priority
Many times, the information stored in the database is encrypted, and privacy becomes a concern. For maximum security, we should encrypt passwords, use authentication to limit database access, and use another server to host the database than the server where the application resides. This will keep your data safe from attacks and privacy violations.
Consider long-term needs
A good database design should be scalable, that is, in the case of increased usage, it can still withstand higher workloads and ensure the operation of applications. For businesses whose workloads may vary, it is critical to keep this in mind when designing databases. For example: if an e-commerce site expects a surge in visitors within a month when sales increase, then this should be taken into account when designing the database so that the database can respond to the rapid increase in visitors and keep working at high operate under load.
code and using stored procedures
One of the common mistakes in database design is not to use stored procedures. Pre-stored routines are pre-stored code strings that are readily available at hand when manipulating data. For example, if an SQL query is a common operation command, it will be easier to write it into a stored procedure ahead of time instead of rewriting it when it is used. Once you have a stored procedure, you can execute and load the SQL query in one step when needed.
Writing a large number of stored procedures is hard work, but if you take the time to do it and document it, it's easier for the end user to use the database.
Invest time in database modeling and design
One of the professional skills of good database design is to invest time and effort in database modeling and design. A common mistake developers make is to ignore this step to save time and focus on other more important aspects of software development. However, database design is critical to ensuring the functionality of the application. If you just want to save time and don't think carefully about the design, you will need to spend more time maintaining the database and even redesigning it in the future.
test design
Testing is also a critical step in database design, and is often overlooked, or even skipped entirely, just to catch up with DDL. We should take the time to thoroughly test the database design before releasing the project to ensure that it meets all planned requirements and is functioning properly.
Epilogue
For data-centric projects, database design is extremely important, and we should also take it seriously during the development process. Database design practices mentioned in the article, such as proper planning for long-term needs, choosing the right database type, using consistent names and labels, data normalization, documenting database design, and testing ahead of time, are all things we excel at in designing. Key issues to consider when using a database.
Original: https://medium.com/quick-code/10-best-database-design-practices-1f10f3441730
This article is translated by CSDN, please indicate the source for reprinting.
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