School of Information Systems

NoSQL Databases vs Relational Databases: A Comprehensive Comparison

22 Oct 2024

In the evolving landscape of database technology, two primary types of databases have gained prominence: NoSQL and relational databases. Each has its unique features, advantages, and use-cases. Relational databases and NoSQL databases are two types of database systems commonly implemented in cloud-native apps. This article will be a comprehensive comparison between NoSQL and relational databases.

What are Relational Database?

Relational databases are based on the relational model proposed by E.F. Codd. They use structured query language (SQL) for defining and manipulating data. Relational databases are characterized by their table-based structure, with each table consisting of rows and columns. Data in these tables are related to each other, and these relationships help in data retrieval and management.

Key Features:

  • Structured Data: Relational databases are ideal for handling structured data.
  • ACID Properties: They ensure Atomicity, Consistency, Isolation, and Durability.
  • Schema: These databases require a predefined schema.

Advantages of relational databases

ACID compliance

Atomicity, Consistency, Isolation, and Durability (ACID) is a standard that guarantees the reliability of database transactions. The general principle is if one change fails, the whole transaction will fail, and the database will remain in the state it was in before the transaction was attempted.

Data accuracy

Using primary and foreign keys allows you to ensure there is no duplicate information. This helps enforce data accuracy because there will never be repeated information

Normalization

The process of normalization involves ensuring the data is organized in such a way that data anomalies are reduced or eliminated. This, in turn, reduces storage costs.

Simplicity

RDMS, or SQL databases, have been around for so long that a wide variety of tools and resources have been developed to help get started and interact with relational databases. The English-like syntax of SQL also makes it possible for non-developers to generate reports and queries from the data.

Disadvantages of relational databases

Scalability

RDMSs are historically intended to be run on a single machine. This means that if the requirements of the machine are insufficient, due to data size or an increase in the frequency of access, you will have to improve the hardware in the machine, also known as vertical scaling.

Flexibility

In relational databases, the schema is rigid. You define the columns and data types for those columns, including any restraints such as format or length.

Performance

The performance of the database is tightly linked to the complexity of the tables—the number of them, as well as the amount of data in each table. As this increases, the time taken to perform queries increases too.

What are NoSQL Databases?

NoSQL, standing for “not only SQL,” refers to databases that store and manage data differently than relational databases. NoSQL databases are designed to handle unstructured data and are known for their flexibility. They can be categorized into four main types: document, key-value, wide-column, and graph databases.

Key Features:

  • Unstructured Data: NoSQL is suitable for unstructured or semi-structured data.
  • Scalability: These databases offer horizontal scalability.
  • Schema-less: NoSQL databases do not require a fixed schema.

Advantages of NoSQL databases

Flexibility in Data Models

NoSQL databases can handle unstructured and semi-structured data, such as JSON, XML, and more. This flexibility is beneficial for applications that deal with diverse data types.

Scalability

They are designed for horizontal scalability, meaning they can handle increased load by distributing data across multiple servers or nodes.

High Performance

NoSQL databases can provide high performance, particularly for read/write operations on large volumes of data, due to their optimized data storage and retrieval mechanisms.

Disadvantages of NoSQL Databases

Data Consistency

While some NoSQL databases offer eventual consistency, this might not be sufficient for applications that require immediate consistency.

Skill Availability

As a relatively newer technology, finding experienced professionals in NoSQL technologies can be more challenging compared to more established SQL databases.

Lack of Standardization

Unlike SQL databases, NoSQL databases lack standardization, leading to variations in queries, data models, and consistency across different NoSQL products.

Difference between Relational database and NoSQL

Relational Database NoSQL
It is used to handle data coming in low velocity. It is used to handle data coming in high velocity.
It gives only read scalability. It gives both read and write scalability.
It manages structured data. It manages all type of data.
Data arrives from one or few locations. Data arrives from many locations.
It supports complex transactions. It supports simple transactions.
It has single point of failure. No single point of failure.
It handles data in less volume. It handles data in high volume.
Transactions written in one location. Transactions written in many locations.
support ACID properties compliance doesn’t support ACID properties
It’s difficult to make changes in database once it is defined Enables easy and frequent changes to database
Schema  is mandatory to store the data Schema design is not required
Deployed in vertical fashion. Deployed in Horizontal fashion.

Conclusion

In summary, NoSQL databases offer great scalability, flexibility, and performance for handling large volumes of diverse data types. However, they may present challenges in standardization, transactional integrity, and complex data analysis. The decision to use a NoSQL database should be based on the specific requirements and constraints of the application and the organization.

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Devyano Luhukay