Learn about relational and nonrelational databases, what they are, the differences between them, and their comparative advantages in helping you to expertly process data.
As we have mentioned in our article about cloud databases, there are different database types depending on how they operate. This is important, as these different types are designed for different applications. In this article, we will talk about two main types of databases today: relational and non-relational databases.
According to Oracle, a relational database is a type of database that stores and provides access to data points that are related to one another. In order to easily track related data, a relational database stores data points along with their attributes in the form of tables. The relationship between each piece of data can easily be determined from its location in the table.
To explain how relational databases work, let us use the spreadsheet as an analogy. For spreadsheets, we store related entries (for example, all sales transactions) in a single sheet. For a single sheet, we define the first column as the name or ID of the data points to be included in each row. Each succeeding column contains the attributes of these data points and are labeled accordingly.
A relational database works similarly:
A relational database will contain at least two relations. These relations contain a different set of attributes but have the same column containing the name or ID, which serves as the connection between seemingly dissimilar relations.
The use of tables, according to Oracle, made it possible to quickly search information through the relations stored in the database. This is why relational databases are one of the most common types of databases in use. One of the most popular implementations of a relational database is the Structured Query Language, or SQL.
Infoworld lists the following strengths of a relational database:
While the weaknesses are as follows:
InfoWorld concludes that relational databases work best for highly structured data and automation of processes.
To clarify further why non-relational databases exist, let us do a quick recap of what structured and unstructured data means.
Structured data is a type of data that is clearly defined and systematically stored in an easily-searchable format. Examples of structured data include personal information records, business transaction records, and customer records.
Unstructured data is a type of data that is not easily searchable and is stored in a variety of formats that cannot be easily processed. Examples of unstructured data include document files, images, and videos.
Databases were initially developed to store structured data.Relational databases, due to their structurally-optimized capabilities, were the perfect method for storing such data. However, recent developments in modern industries have led to a greater need for storing unstructured data types. Non-relational databases were developed for this purpose. We will highlight five types of non-relational databases:
Seeing that there is a wide variety of database types now available, you would need to determine the type of data that you need to store so you can make a good choice. Below is a quick summary of each type of data along with the database type they are best designed for:
Each type of database has its strengths and you can choose the database type that best fits your individual needs.
-Database Basics: Everything You Need to Know
-Unstructured Data: How to Deal With It
What is a Relational Database Management System?
How to choose the right database for your enterprise
ACID Explained: Atomic, Consistent, Isolated & Durable – BMC Software | Blogs
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Structured vs Unstructured Data: 5 Key Differences
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Relational databases vs Non-relational databases
Relational vs. Non-Relational Database: Pros & Cons | The Aloa Blog
What is NoSQL? | Nonrelational Databases, Flexible Schema Data Models | AWS
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