In the ever-evolving world of Enterprise Resource Planning (ERP), the choice between SQL and NoSQL databases is a critical decision that can significantly impact the performance and scalability of your applications. Ranking of the most popular database management systems worldwide, as of September 2023.

SQL in ERP solutions has its unique strengths and are suited to different types of data and access patterns.

In this blog, we will delve into the key differences between SQL and NoSQL databases, their pros and cons, and how they fit into the ERP landscape.

Let’s go.

SQL Database : Overview

SQL, which stands for Structured Query Language, is used for relational databases. A SQL database is a collection of tables that store a specific set of structured data. Each row in these tables reflects a data entity, and every column defines a specific information field.

ERP solutions using SQL have been used for decades and have grown in popularity, becoming one of the most common data management tools. They provide the user with an efficient way to store the data and an intuitive way to access or modify it.

In a SQL database, there are internal consistency checks to ensure any new data added to the database conforms to predefined data types.

For example, Each book has a title, author, publication year, etc. (columns). Now, each book is unique, right? It has its own identity – that’s what we call a unique key in SQL databases.

SQL databases are like this library. They store data in a structured way, making it easy for you to find exactly what you’re looking for. Just like how you’d look for a book by its title or author, in SQL databases, you can retrieve data based on different attributes.

And the best part? SQL databases ensure that everyone can read their favourite book (data) without disturbing others. So even if your friends are at the library at the same time, you all can enjoy your reading without any interference.

In short, SQL databases are like well-organised libraries for your data. They make storing, retrieving, and managing data a breeze! These properties make ERP and SQL a formidable union.

Pros of SQL Databases

1. Faster Query Processing: SQL databases are known for their speed. They can retrieve large amounts of data quickly and efficiently. Operations like insertion, deletion, and manipulation of data are also done in almost no time.

• No Coding Skills Required: With SQL, you don’t need to write a lot of code to retrieve data. It uses basic keywords such as SELECT, INSERT INTO, AND UPDATE, etc., making it a user-friendly language.
• Standardised Language: SQL provides a uniform platform worldwide to all its users due to its documentation and long establishment over the years.

• Portability: SQL can be used in programs in PCs, servers, laptops independent of any platform (Operating System, etc.). It can also be embedded with other applications as per need/requirement/use.

• Security: SQL databases have built-in security features that help protect data from unauthorised access, such as user authentication, encryption, and access control.

• Scalability: SQL databases can handle large volumes of data and can be scaled up or down as per the requirements of the application.

Cons of SQL Databases

1. Pricing of Premium Packages: If you’re planning to use an enterprise-grade SQL-based database platform, you’ll have to pay for the privilege². There are open-source options out there as well, but they lack the functionality and support of their premium counterparts.

• Concerns Over Security: Over the years, SQL databases have been used as a point of entry for hackers looking for backdoors into mission-critical business systems². This means you need to be eternally vigilant for attacks, and invest enough in security to minimise the risks.

• Steep Initial Learning Curve: While SQL may be a comparatively simple programming language to learn, it also suffers from having a steep learning curve at first². This is partly a result of the superficial complexity of query structures, and the possibility for a lot of variety in the way that certain actions are completed².

When to Use SQL Databases

1. Structured Data: SQL databases are a great choice when you’re dealing with structured data. They allow you to define a schema that specifies the structure of your data, including the tables, columns, and relationships.

• Data Integrity: If maintaining data integrity is a priority for your application, SQL databases are the way to go. They have built-in mechanisms to ensure that the data stored in the database is valid and consistent.

• Complex Queries: SQL databases shine when it comes to executing complex queries. They provide a powerful query language that allows you to retrieve and manipulate data in sophisticated ways.

When to Avoid SQL Databases

1. Unstructured Data: If you’re dealing with unstructured or semi-structured data, SQL databases might not be the best fit. They require a predefined schema, which can be limiting when dealing with data that doesn’t fit neatly into a table.

• Scalability: While SQL databases can handle large volumes of data, they might not be the best choice if you need to scale your application horizontally. NoSQL databases are typically better suited for horizontal scaling.

• Rapid Development: If you’re working in a fast-paced development environment where the structure of your data is likely to change frequently, SQL databases might slow you down. They require you to define a schema upfront and make changes through migrations, which can be time-consuming.

Now that we have an idea on what SQL is, let’s peek into what NoSQL has to offer.

What is a NoSQL Database?

NoSQL databases, also known as “not only SQL”, “non-SQL”, or “non-relational” databases, are a type of database management system (DBMS) that provides a mechanism for storage and retrieval of data.

Unlike traditional relational databases that use tables with predefined schemas to store data, NoSQL databases use flexible data models that can adapt to changes in data structures and are capable of scaling horizontally to handle growing amounts of data.

NoSQL databases come in a variety of types based on their data model. The main types are document, key-value, wide-column, and graph. They provide flexible schemas and scale easily with large amounts of data and high user loads.

NoSQL databases are often used in applications where there is a high volume of data that needs to be processed and analysed in real-time, such as social media analytics, e-commerce, and gaming. They can also be used for other applications, such as content management systems, document management, and customer relationship management.

Pros of NoSQL Databases

1. Flexible Schema: Unlike relational databases, NoSQL databases easily store and combine any type of data, both structured and unstructured. You can also dynamically update the schema to evolve with changing requirements and without any interruption or downtime to your application.

• Elastic Scalability: NoSQL databases scale out on low-cost, commodity hardware, allowing for almost unlimited growth. This is particularly useful in today’s world where outward scalability is replacing upward scalability.

• High Performance: NoSQL databases are built for great performance, measured in terms of both throughput and latency. They are a good choice when there are large amounts of data or ever-changing data sets.

• Database Maintenance: NoSQL models need much less expert management as they already have auto repair and data distribution capabilities, fewer administration and tuning requirements as well as simplified data designs.

• Economical: NoSQL models are easy and cheap to install. This means that more data can be processed and stored at a very minimal cost.

Cons of NoSQL Databases

1. Not Mature: Relational models have been around for some time now compared to NoSQL models and as a result, they have grown to be more functional and stable systems over the years.

• Less Support: Every business should be reassured that in case a key function in their database system fails, they will have unlimited competent support any time. All relational model vendors have gone the extra mile to provide this assurance and made it sure that their support is available 24 hours which is not a step yet guaranteed by

NoSQL vendors.

• Business Analytics And Intelligence: Most NoSQL features are focused on meeting the demands of modern-day web 2.0 web applications, ignoring the demands of apps made without these characteristics hence end up offering fewer analytic features for normal web apps.

When to Use NoSQL Databases

1. Handling Large Amounts of Data: NoSQL databases are a good choice when you’re dealing with large amounts of data. They are designed to handle big data and provide fast querying and processing capabilities.

• Flexible and Rapid Development: NoSQL databases have flexible schemas that can adapt to changes in data structures. This makes them a good choice for applications that need to evolve rapidly.

• Scalability: If you need to scale your application horizontally to handle growing amounts of data, NoSQL databases are a great choice. They are designed for horizontal scalability, which allows them to handle more traffic by adding more servers in your NoSQL database.

• Performance: If performance is a key requirement for your application, NoSQL databases might be the right choice. They are built for great performance, measured in terms of both throughput and latency.

When to Avoid NoSQL Databases

1. Complex Transactions: If your application requires complex transactions with multiple operations, SQL might be a better choice. NoSQL databases do not typically provide the same level of transactional consistency as SQL databases.

• Mature Tooling and Support: SQL databases have been around for a long time and have a mature ecosystem of tools and support. If you rely on these tools or need extensive support, SQL might be a better choice.

• Structured Data: If your application primarily deals with structured data that fits well into tables, SQL databases might be more appropriate.

Want to know how these factors can affect an ERP solution? Check out our case study on

 Kerchanshe Farms.

Major Differences Between SQL and NoSQL

1.  Data Structure

SQL databases are primarily called Relational Databases (RDBMS); whereas NoSQL databases are primarily called non-relational or distributed databases.

In SQL databases, data is stored in tables, which is a collection of related data entries and it consists of columns and rows.

Here’s a simple example of a SQL query that creates a table:

On the other hand, NoSQL databases store data in several ways: it could be column-oriented, document-oriented, graph-based or organized as a KeyValue store. For instance, here’s how you might store data in a NoSQL database like MongoDB:

2.  Scalability

In general, SQL databases can scale vertically, meaning you can increase the load on a single server by increasing things like RAM, CPU, or SSD. On the other hand, NoSQL databases are horizontally scalable. This means that you handle more traffic by sharding, or adding more servers in your NoSQL database.

3.  Language

SQL databases define and manipulate data-based structured query language (SQL). For example:

NoSQL databases have dynamic schemas for unstructured data. The syntax varies from database to database, and you can add fields as you go. Here’s an example of querying documents in a MongoDB NoSQL database:

4.  ACID vs CAP

SQL databases follow ACID properties (Atomicity, Consistency, Isolation, and Durability) whereas the NoSQL database follows the Brewers CAP theorem (Consistency, Availability, and Partition tolerance).

SQL vs NoSQL Database Security Comparison

SQL

SQL databases have matured over the years, resulting in robust security features. They provide mechanisms to ensure data integrity and consistency. SQL databases also support ACID properties (Atomicity, Consistency, Isolation, Durability), which are crucial for ensuring reliable processing of transactions.

SQL databases provide extensive access control mechanisms. You can define roles and grant specific permissions to each role. This allows you to control who can access what data and what they can do with it.

For instance, SQL Server provides a layered security methodology that leverages multiple security capabilities targeted at different security scopes. The security features made available in SQL Server 2016, and improved in subsequent releases, help counter security threats and provide well-secured database applications

Here’s an example of how you might grant permissions in a SQL database:

NoSQL

NoSQL databases have fewer inbuilt security features to allow faster data access. They lack confidentiality and integrity attributes. Also, as they don’t have a fixed and well-defined schema, you can’t segregate the permissions.

However, NoSQL databases are not entirely devoid of security features. They do provide mechanisms for ensuring data confidentiality and integrity. Also, some NoSQL databases offer features like encryption at rest and in transit, role-based access control, auditing, and more.

For instance, MongoDB offers advanced security features such as authentication with integration with external security mechanisms including LDAP, Windows Active Directory, Kerberos and x.509 PKI certificates. It also provides user-defined roles which means you can configure granular permissions for a user or application based on the privileges they need to do their job.

Here’s an example of how you might handle security in a MongoDB NoSQL database:

So what’s your choice?

Choosing between SQL and NoSQL for your ERP system is not a matter of which is better, but rather which is more suited to your specific needs. Both have their strengths and weaknesses, and the right choice depends on your data structure, scalability requirements, and the complexity of your transactions. It’s crucial to understand these factors to make an informed decision that will drive your business forward.