SQL vs. NoSQL: Which Database to Choose?

There are two primary databases that are generally used for storing digital data: SQL and NoSQL. From engineers and IT decision-makers to analysts, everyone is familiar with relational and non-relational databases. Both methods are used to store data effectively, but they vary in their structures, relationships, scalability, language, and support. 

However, the large variety and depth of database systems in today’s world can be very dizzying. With the increased amount of unstructured data, the processing power, the availability of storage, and the transforming analytic requirements have ignited interest in different technologies. 

NoSQL is an alternative to traditional Relational Database Management Systems. 

Thus, it is important to know in detail how NoSQL differs from SQL. This is the reason we are writing this blog today. 

Let’s find out about each type of database, how they are similar and different, and how to find out which type of database is suitable for your application. 

A-Z About SQL and NoSQL

SQL

SQL stands for Structured Query Language. It is a programming language for technical and non-technical-minded users to query, control, and change data in a relational database. It uses a relational model that is well-organized into columns and rows and works marvelously with well-defined structured data like those where relations exist among different entities. 

In a SQL database, the tables are connected through foreign keys and develop relations between tables and fields, for example, the employees and the department. 

In addition to this, SQL databases are vertically scalable, which means one can increase the load by adding more storage components like RAM or SSD. 

SQL Functions:

• Retrieval of the Database
• Can perform queries on the database
• Insert records in the database.
• Delete records from a database.
• Can set permissions on tables and views
• Can create new tables in a database
• Can also create stored procedures.

NoSQL

A NoSQL database is a non-relational database, hence “No” in its name; it is also defined as “Not only SQL.” 

But wait, it doesn’t mean the system doesn’t use SQL. Non-relational implies that they can store data in a way other than tabular relations. The SQL database is used for structured data, whereas NoSQL is suitable for structured, semi-structured, and unstructured data. 

Thus, NoSQL doesn’t adhere to a rigid schema and has more versatile structures to accommodate the different data types. 

Other than that, NoSQL databases make use of varying query languages; sometimes they don’t even have a query language. 

The NoSQL database works wonders with unstructured data and is schema-less. They use non-tabular data models, that are document-oriented or graph-based. 

SQL vs. NoSQL: Key Features

SQL

• Gives high-performance capabilities
• It is highly compatible with all kinds of RDBMS, such as MySQL, SQL Server, Oracle Database, MS Access, and more.
• Provides vertical scalability
• Manages large transactions with efficiency.
• Provides robust security measures like rigid schema, data consistency, data integrity, and regular updates.
• Best suited for all types of organizations.
• It is easy to learn and manage.
• It is an open-source programming language.
• SQL supports the data definition language and the data manipulation language for the database query.

NoSQL

• It is more scalable than any other database management system.
• It is schema-free which means, you don’t have to define the schema before storing the data in the system.
• NoSQL also makes it easy to distribute the data to more than just one device.
• With a NoSQL database, you don’t require data normalization.
• It has a simple API for easy user interfaces.
• The good thing is that it can store unstructured, semi-structured, and structured data.

SQL vs. NoSQL: Main Differences

Let’s get to the main point, which database to choose?

To decide which database you should choose, you have to know the major differences between them. It will make things a little clearer, and it will also make it easier for you to choose.

So, here we will use five practical points to differentiate SQL from NoSQL. 

1. Language

SQL is very old, so it is recognizable, well-documented, and widely used. It’s versatile, pretty safe to use, and well-suited for complex queries. But, SQL also restricts its users from working in a pre-defined tabular schema. 

However, NoSQL databases allow the representation of alternate structures, alongside each other, encouraging greater flexibility. NoSQL emphasizes less planning and gives freedom to add new attributes, and fields, as well as the possibility of varied syntax across the database. 

As a group, NoSQL languages are devoid of the standard interface that SQL offers, so in NoSQL, it gets difficult to execute more complex queries. 

While querying a relational database, competency in one language translates to proficiency in others. Moreover, there is very little consistency between the NoSQL languages, as they have a diverse set of unrelated technologies. Various NoSQL databases have a unique data manipulation language bound by particular structures and capabilities. 

2. Scalability

SQL databases can be scaled vertically, whereas NoSQL databases use a primary-secondary architecture, so they scale well horizontally.  

“Vertically scalable”  means that you can maximize the load on a single server by increasing things like RAM, CPU, or SSD. 

In the case of NoSQL, you have to handle the traffic by sharding or partitioning your NoSQL database. 

So it is somewhat like adding more blocks to already stacked blocks versus adding more blocks to the neighbourhood. This makes NoSQL larger and more powerful, making it the preferred choice for larger data sets. 

3. Structure

SQL database schema always depicts relational, tabular data, with rules on consistency and integrity. They contain tables with columns and rows, and the keys have strained logical relationships. 

Whereas NoSQL does not follow this format, it has four broad categories viz column-oriented, key-value, document, and graph. 

4. Properties

SQL and NoSQL obey different rules for resolving transactions. The SQL database follows ACID properties (atomicity, consistency, isolation, and durability), whereas the NoSQL database follows the CAP theorem (consistency, availability, and partition tolerance). 

5. Support and Communities

Since it’s 40 years old, the SQL database has held massive communities, stable codebases, and proven standards. Tons of examples are posted online, and experts are available to support those who are new to programming relational data. 

NoSQL technologies are getting adopted quickly, but their community is smaller. The SQL languages are associated with large vendors, while NoSQL benefits from open systems.  

Differentiating Factors	SQL Databases	NoSQL Databases
Data Storage Model	Tables with fixed rows and columns	Document: JSON documentsKey-value: Key-value pairsWide-column: tables with rows and dynamic columnsGraph: nodes and edges.
Development History	Developed in the 1970s with the aim of reducing data duplication.	It was developed in the late 2000s and focused on scaling and allowing rapid application changes driven by Agile and DevOps practices.
Primary Purpose	The general purpose	Document: general purpose, Key-value: large amounts of data with simple lookup queries,Wide-column: large data with predictable query patterns. Graph: Analyzing and traversing relationships in the connected data.
Schemas	Rigid	Flexible
Scaling	Vertical	Horizontal
Joins	Mostly required	Not required
Data to Object Mapping	Requires ORM	Might not require ORMs. The MongoDB documents map directly to data structures in popular programming languages.
Examples	Oracle, MySQL, Microsoft SQL Server, and PostgreSQL	Document: MongoDB and CouchDBKey Value: Redis and DynamoDBWide-column: Cassandra and HBase,Graph: Neo4j and Amazon Neptune
Properties	Follows ACID properties	Follows CAP properties

When to Use SQL

SQL is the best choice when working with related data. Relational databases are efficient, flexible, and can be accessed easily from any application. When one user updates a specific record, every instance of the database gets refreshed automatically, and this information is provided in real-time. It can be considered one of the benefits of a relational database.  

You can handle large amounts of information easily with SQL and relational databases and can allow flexible access to the data once instead of changing multiple files. It’s great for assessing data integrity. 

Big companies like Uber, Netflix, and Airbnb use SQL. Even major organizations like Google, and Amazon have built their own database systems using SQL to query and analyze data. 

When to Use NoSQL

NoSQL is considered good when it is more crucial that the availability of big data be fast. It can also be used when a company wants to scale due to changing requirements. 

Either way, NoSQL is easy-to-use, flexible, and offers good performance. 

When you are dealing with large data sets or flexible data models, use NoSQL. For large amounts of unstructured data and document databases (like CouchDB, MongoDB, and Amazon DocumentDB), NoSQL is a good fit. 

The NoSQL databases are scalable, and they allow horizontal scaling. Cassandra is one of the NoSQL databases developed by Facebook, it handles massive amounts of data spread across various servers with no single point of failure. 

Other than Facebook, Amazon, Google, and Netflix use NoSQL systems for their extensive datasets. 

How Extern Labs Helps With SQL/NoSQL Database Integration

If you have decided which database to use between SQL and NoSQL, now you have to move the data into them. 

However, data integration is a complex process. If you do it wrong, you can lose valuable data sets or even face fines for non-compliance with data governance frameworks. 

Extern Labs can help you with Data integration, whether you choose SQL or NoSQL. Get world-class tech services and easy data transformations with Extern Labs.