The two types of database systems used in cloud-native apps are relational and NoSQL. They’re created in different ways, store data in different ways, and are accessed in diverse ways. We’ll look at both in this part.
Table of Contents
What is a Relational Database?
For decades, relational databases have been a popular technology. They’re well-established, well-proven, and frequently used. There are a plethora of database products, tools, and experiences to choose from. Relational databases keep track of data tables that are linked to one another. These tables have a defined structure, handle data with SQL (Structured Query Language), and provide ACID guarantees.
What is NoSQL Database?
High-performance, non-relational data storage are referred to as No-SQL databases. They stand out for their simplicity of use, scalability, robustness, and availability. NoSQL stores unstructured or semi-structured data, generally in key-value pairs or JSON documents, rather than combining tables of standardized data.
Further, most No-SQL databases do not satisfy ACID guarantees. Different NoSQL Databases are preferred by high-volume services that demand sub-second response times.
Difference Between Relational and NoSQL Database
| NoSQL Database | Relational Database |
|---|---|
| NoSQL Database supports a very basic query language. | Relational Databases support a Strong query language. |
| There is no set schema in a NoSQL database. | A fixed schema exists in a relational database. |
| The consistency of a NoSQL database is only achieved over time. | Relational databases follow acid characteristics. (Consistency, Separation, and Durability) |
| NoSQL databases do not support transactions (support only simple transactions). | Transactions are supported by relational databases (also complex transactions with joins). |
| To manage data that comes in at a high rate, a NoSQL database is employed. | When dealing with data that comes in at a slow rate, a relational database is employed. |
| The data in NoSQL comes from a variety of sources. | The data in a relational database comes from a single or a few sources. |
| Structured, unstructured, and semi-structured data can all be stored in a NoSQL database. | Only structured data is stored in a relational database. |
| There is no single point of failure with NoSQL databases. | With failover, relational databases have a single point of failure. |
| NoSQL databases hold the capability of handling huge amounts of data. | Relational databases are used to manage data with a modest amount of volume. |
| The structure of NoSQL is decentralized. | The structure of a relational database is centralized. |
| Both read and write scalability are provided by NoSQL databases. | Only read scalability is provided by relational databases. |
| A horizontal deployment of a NoSQL database is used. | A vertical deployment of a relational database is used. |
When would You use NoSQL Database vs. Relational Database?
When to use NoSQL Database?
Use Cases
- Close the Gap Between Developers and Security
The quantity, size, and quickly changing nature of data being kept has revealed vulnerabilities in traditional databases with Web 2.0 and Big Data development. Relational databases have struggled to cope with the reality of modern computing and its enormous volume of data. They are well-suited for the tasks for which they were initially created.
- Flexible Data Requirements
The capacity to manage flexible data storage is one of NoSQL’s strongest features. Traditional RDBMS rely on a static data structure; in fact, best practices dictate that a database schema be established before any coding takes place. The reason for this is obvious: altering the database structure afterwards may be time-consuming and costly.
- Scalability and Rapid Data Growth
The capacity of NoSQL to handle unpredictable data expansion is another area where it excels. The necessity for NoSQL is exemplified by scenarios involving the introduction of a new software or service, in which a company’s client base might rapidly surge into the millions.
These features allow scaling out a NoSQL database to keep rapid growth considerably faster and frequently cheaper.
When To Use Relational Database?
Use Cases
- Flexibility and Rapid Data Growth
A relational database management system (RDMS) is built to scale vertically. When a database’s performance begins to suffer, the most frequent remedy is to move it to a larger hard drive or a faster server. However, in the current era of Big Data, the database’s fast expansion often outpaces the time at which such a laborious transfer can be completed.
- Performing at the Same Time
To maintain data integrity, many conventional databases include a locking mechanism. The RDMS marks data before starting a transaction so that no other process may change it until the transaction succeeds or fails. Unfortunately, in a big database with tens of thousands of users, such a method significantly influences database performance.
Conclusion
A relational database is still the best solution for businesses that need to hold predictable, organized data with a limited number of persons or apps accessing it. It has a degree of maturity and extensive acceptance that no other NoSQL alternatives, or any other alternatives, can match.
In any of these instances, NoSQL’s decentralized nature, both in terms of database structure and storage technology, makes it a far superior alternative to conventional databases.
