Document Database VS Relational Database

Explore the key differences between document databases and relational databases, including data model, querying capabilities, scalability, ease of use, and use cases. Check the comparison between document database and relational database in order to make the best decision for your application needs.

What is Document Database?

A document database, also known as a document-oriented database, is a type of NoSQL database that stores data in the form of documents, rather than in tables with rows and columns like a traditional relational database. These documents can be in a variety of formats, such as JSON, BSON, or XML. They often include nested data structures, which can make it easier to store and query complex data. Document databases are well suited for storing semi-structured data and are often used in web and mobile applications. They offer a flexible schema and high performance, but may have limited querying capabilities compared to relational databases and difficulties with data consistency and validation.

What is relational database?

A relational database is a type of database management system that stores data in tables with rows and columns. The tables are related to each other through a system of keys and constraints, allowing for the creation of complex queries and data relationships. The most common type of relational databases are SQL databases which use a language called SQL (Structured Query Language) to interact with the database.

In a relational database, data is split across multiple tables to eliminate data redundancy and improve data integrity. The relationships between the tables are established using foreign keys. Relational databases provide a robust querying mechanism, data validation, and data integrity features. However, they may have a steeper learning curve and require more expertise to use effectively, and may not be as flexible as document databases when dealing with unstructured or semi-structured data.

Document database vs relational database

Document databases and relational databases are both types of databases, but they have some key differences:

Data Model:

A document database stores data in the form of documents, which can include nested data structures. Each document can have a unique structure and can contain different fields.
A relational database stores data in tables with rows and columns, with a fixed schema. Data is split across multiple tables to eliminate data redundancy and improve data integrity.

Querying:

Document databases may have limited querying capabilities compared to relational databases, particularly when it comes to performing complex, multi-table joins.
Relational databases have a powerful querying language (SQL) that allows for complex data retrieval and joins across multiple tables.

Data validation:

Some document databases may not have built-in support for data validation, which can make it difficult to ensure data consistency and integrity.
Relational databases have a robust data validation mechanism to ensure data consistency and integrity.

Scalability:

Document databases are often horizontally scalable, which means that they can handle a large amount of data and a high number of concurrent users.
Relational databases can also be horizontally scalable but it’s more complex than document databases.

Ease of use:

Many document databases have a simple and intuitive API, which can make them easy to use and integrate into existing applications.
Relational databases may have a steeper learning curve and require more expertise to use effectively.

Use cases:

Document databases are well suited for storing semi-structured or unstructured data, and nested data structures, such as JSON or XML documents.
Relational databases are well suited for structured data, complex queries and data integrity.

In summary, both document databases and relational databases have their own advantages and disadvantages, and the choice of which one to use will depend on the specific needs of your application.