April 24, 2023

Relational and Non-relational Databases: Which One Is Right for Your Application?

As a developer, choosing the right database for your application is crucial for ensuring optimal performance, scalability, and data consistency. Regarding databases, there are two main types: relational (SQL) and non-relational (NoSQL).

In this article, we'll explore the differences between these two types of databases and guide you on when to use each.

Relational Databases (SQL)

Relational databases are structured and store data in tables with predefined schemas. They use SQL (Structured Query Language) to perform queries and manipulate data. Relational databases are well-suited for applications that require complex querying, transactions, and data consistency. Examples include financial transactions, e-commerce, and content management systems.

One of the main benefits of using a relational database is its ability to enforce data consistency through transactions. Transactions allow multiple operations to be grouped and treated as single atomic units. This ensures that all operations within the transaction are either completed successfully or rolled back if an error occurs, ensuring data consistency. 

It's worth noting that MongoDB has had this feature since 2018 with version 4.0, making it a viable alternative for applications that require transactional support. Another advantage of using a relational database is its ability to handle complex queries efficiently. Relational databases are designed to handle joint operations between tables, making them well-suited for complex data relationship applications.

Non-Relational Databases (NoSQL)

Non-relational databases store unstructured data in flexible formats like documents, key-value pairs, or graphs, making them highly scalable and adaptable without needing a predefined schema.

NoSQLs are suitable for applications requiring scalability, low latency, and unstructured data storage, such as big data, real-time analytics, and content distribution. Non-relational databases efficiently handle large volumes of unstructured data and perform high read/write loads, especially when distributed to scale horizontally.

A comparison table highlights the primary characteristics of relational and non-relational databases concerning factors like scalability, query language, ACID compliance, schema changes, performance, and cost. However, there may be variations within each category.

When to Use Each Type of Database 

A relational database might be best if your application requires complex querying and structured data. On the other hand, If your application requires high scalability and unstructured data, a non-relational database might be the better choice. Let's look at some scenarios where each type of database might be more appropriate.

USQL databases when:

  • Your data has a well-defined structure and schema that is unlikely to change frequently.
  • You need to enforce strict data consistency and integrity.
  • You need to perform complex queries to join and aggregate data from multiple tables.
  • You need to handle large amounts of structured data, such as financial transactions, inventory, or customer information.
  • Your application needs ACID compliance, ensuring reliable and consistent transaction processing, even during errors or system failures. MongoDB has ACID features, making it a viable alternative for ACID-requiring applications.

Use NoSQL databases when:

  • Your data is unstructured or semi-structured and has variable or dynamic schemas.
  • You need to store large volumes of data that may not fit well into a relational database model.
  • Your application requires high scalability and availability, where data can be easily partitioned and distributed across multiple servers and clusters.
  • Your application needs flexible data modeling and can tolerate eventual inconsistency, where data may not be immediately consistent across all nodes. This depends on how replicas are updated and apply to any database type.
  • You must handle unstructured data such as text, media, or machine-generated data like sensor readings.

The following table presents the pros and cons of SQL and NoSQL databases as a summary of the information presented in this article, allowing a quick comparison of the two types. However, it may only cover some aspects of each database type, and the importance of each factor may vary depending on the specific use case.

The Takeaway on SQL and NoSQL

SQL databases are ideal for structured data with complex relationships and require strict consistency. In contrast, NoSQL databases are more suitable for unstructured or semi-structured data that need high scalability and flexibility. 

Ultimately, the choice between the two depends on your specific needs, the complexity of your data schema, and your application requirements.

Evaluating the trade-offs between consistency and scalability is essential for choosing a database system that can meet your business goals and grow with your data needs.