Relational Vs Non relational database

What are databases

Databases are designed for easy access, management, and updating of data, and they can contain various types of data including words, numbers, images, videos, and files. Companies use databases, including cloud databases, for a multitude of purposes, such as:

What is a Relational Database (SQL Database)

A relational database organises data into tables, which are made up of rows and columns. Each row in the table represents a unique record, and each column represents a specific attribute of the data. The key feature of a relational database is the ability to create relationships between these tables, allowing data to be linked and organised in a structured manner.

The relationships in a relational database are established using keys. A primary key is a unique identifier for a record in a table, while a foreign key is a field in a table that matches the primary key of another table. These keys enable the creation of relationships between tables, which can be one-to-one, one-to-many, many-to-one or many-to-many.

SQL (Structured Query Language) is the language used to interact with a relational database. It allows users to create, read, update, and delete data in the database. SQL is used to write queries to extract specific data, join tables, and perform complex calculations. It's also used to enforce data integrity and security rules in the database.

When to use relational vs. non-relational databases

Choosing between relational databases, also known as SQL (Structured Query Language) databases, and non-relational databases known as NoSQL (Not Only SQL) databases, depends on the specific requirements of your project. Both types of databases have their strengths and are better suited to different kinds of tasks.

SQL databases are relational, meaning they organise data into tables. Each table has a predefined schema, which means the structure (columns and their types) must be set before you can store data.

If your data fits well into a table structure and won't change frequently, an SQL database might be a good choice. SQL databases support ACID (Atomicity, Consistency, Isolation, Durability) properties, making them a good fit for systems where transactions are complex and data integrity is critical, such as banking systems.

Relational databases are also a good choice when data integrity is a priority: SQL databases support constraints such as unique, primary, and foreign keys which help maintain data integrity.

NoSQL databases are non-relational, meaning they do not rely on a traditional table structure and have dynamic schemas for unstructured data. They can store data in various ways: document-oriented, column-oriented, graph-based, or key-value pairs.

NoSQL databases are ideal for situations where data is unstructured or semi-structured. If your data doesn't fit well into table structures or if the data structure changes frequently, a NoSQL database might be a good choice. NoSQL databases are designed to scale out by adding more servers to the network. This makes them a good fit for large-scale data storage needs.

Non-relational databases can provide faster performance for specific use cases, such as big data and real-time applications.

The need for NoSQL databases emerged primarily due to the limitations of traditional relational databases in handling the vast amounts and types of data generated by modern applications, particularly in the context of the internet and web applications. As the volume, velocity, and variety of data increased, it became clear that the rigid schema and scalability constraints of relational databases were not well-suited to the needs of many contemporary use cases.

Relational databases, which had been the standard for decades, were designed for structured data and had a fixed schema that required data to be stored in tables with predefined columns. This structure made it difficult to accommodate the unstructured or semi-structured data that is common in big data applications, such as social media, mobile, and Internet of Things (IoT) data. Moreover, the scale of data and the need for high availability and fault tolerance in distributed systems posed significant challenges for relational databases.

NoSQL databases, on the other hand, offer flexible data models. This flexibility enables developers to iterate more quickly and to handle a wide variety of data types without the need for complex data transformation.

Additionally, NoSQL databases are designed to scale out by distributing data across multiple servers, providing the ability to handle large volumes of data and high user loads while maintaining performance. This distributed nature also contributes to higher availability, as the system can continue to operate even if some nodes fail.