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The Dummies’ Guide to SQL vs NoSQL
Data is the new oil.
Over 2.5 quintillion bytes of data are generated every day, and the ones who can make sense of this vast information have the power to drive businesses. That’s why developers, engineers, and all tech enthusiasts are trying to decipher the binaries of the digital world into crunchable bites.
SQL and NoSQL are two programming languages that help fetch, alter, and maintain large databases. This article will act as a guide for beginners and experts to understand SQL vs NoSQL, their differences and advantages (without overwhelming you with jargon).
Table of Contents
What is SQL?
Let’s start with the basics.
SQL stands for Structured Query Language.
But what does this actually mean?
SQL is a programming language used to store, fetch, edit, update, and delete the database that is maintained in the form of rows and columns. That’s why it’s called a relational database, where the data is identified with the corresponding rows and columns.
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Key features of SQL
- It is a documented, set query language that makes learning it easier. Even non-technical people can master it.
- It is compatible with all types of relational database management systems, like MySQL, Oracle, MS Access, etc.
- It is an open-source programming language, meaning global developers can enhance it further without users bearing any cost.
- It can deal with heavy data transactions effectively.
- It can be used by small or large organizations alike.
Drawbacks of SQL
- A few versions of SQL are expensive, which can limit its reach to a wider user base.
- There are security and privacy compliances that users have to follow, limiting their access to the database.
- SQL has a significant setback in writing complex queries since it follows strict query syntax.
What is NoSQL?
NoSQL stands for “not only SQL.” It is a type of database that is not based on the traditional relational database model. It can be in graphs, documents, or key-value pairs. It’s more suitable for unstructured or semi-structured databases with room for flexibility.
Key features of NoSQL
- NoSQL has higher scalability because there isn’t rigidity around data storage. It can be unstructured, and there is no need to add data into the schema before use.
- It allows horizontal scalability, where you can add data clusters as nodes.
- Developers can use simple APIs for building user interfaces.
- You can distribute data on more than one device simultaneously.
- Since it doesn’t require the addition of complex hardware, it’s an overall low-cost investment.
Drawbacks of NoSQL
- Since it doesn’t follow ACID (Atomicity, Consistency, Isolation, and Durability) properties, reliability and security can pose a challenge.
- An absence of well-documented and fixed query language makes it hard for a beginner to work around.
- As it is fairly new, there are a few improvements required in the cross-platform support system.
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What is the difference between SQL & NoSQL?
Parameter
SQL
NoSQL
Database Storage
The data is stored in a static form
The data is available in a dynamic manner
Data Representation
The data is represented as a table in the form of rows and columns
The data is represented as key-value pairs, graphs, or wide-column stores
Scalability
It allows vertical scalability where new rows can be added
It allows horizontal scalability where data is added as nodes
Source
It is entirely open-source
It is a mix of open-source and privatization
Implementation
It observes ACID (Atomicity, Consistency, Isolation, and Durability) properties for its data management
It is based on CAP (Consistency, Availability, and Partition Tolerance) properties
Syntax
It follows a well-documented, and universal syntax called structured query language
It doesn’t have a fixed query language. The syntax differs from database to database
Database Examples
Some of the popular SQL databases are Oracle, MySQL, Amazon RDS, Google Cloud SQL, Microsoft Azure, etc.
Some of the popular NoSQL databases are MongoDB, Oracle NoSQL, Redis, HBase, Apache’s CouchDB, etc.
Network
You can use it on a commodity network like ethernet
You can use it on a highly available network like Fabric Path
Hierarchical Data
SQL doesn’t support hierarchical data storage
NoSQL supports hierarchical data storage
When to Use SQL
1. When Your Data is Structured
If you are dealing with data that is static in nature and doesn’t change, then using SQL will get the job done effectively. You can use it if you are not expecting high data traffic that would require additional servers.
2. If Security is Your Priority
If you need to comply with the ACID (Atomicity, Consistency, Isolation, and Durability) properties, then you should definitely choose SQL as it ensures that even large data transactions are secure and consistent.
When to Use NoSQL
1. When Your Data is Unstructured
If you expect massive growth with your data, then using NoSQL is a wiser choice because it allows you to work with unstructured data. So even if you want to work with hierarchical data, you can do so easily with NoSQL.
2. If Flexibility is Your Priority
NoSQL observes CAP (consistency, availability, partition tolerance) properties to manage data, giving users much more flexibility to manage and manipulate data. Also, the syntax isn’t rigid and depends on the database you are working on. It allows developers to utilize their full potential and run even complex queries.
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How to Get Started With Your Career?
Depending on your goal and the projects you want to work on, start with learning the skills. But merely brushing up on the theoretical stuff won’t take you places. The sure shot way to success, especially as a developer, is having practical knowledge.
But how will you get projects as a newbie?
Ellow can help you here. It’s a platform where global talent and recruiters come together to work on exciting projects. Developers can explore opportunities tailored to their skills, and companies have the opportunity to hire quality talent from a global pool.
FAQs on SQL vs NoSQL
SQL or Structured Query Language was developed as early as 1970.
NoSQL can’t replace SQL, and both have their own importance and use
Some of the common SQL databases used globally are: Db2, MySQL, PostgreSQL, YugabyteDB, CockroachDB, Oracle Database, Microsoft SQL Server, Azure SQL Database, etc.
Some of the common NoSQL databases used across industries are: Redis, FaunaDB, CouchDB, MongoDB, Cassandra, Elasticsearch, BigTable, Neo4j, HBase, etc.
SQL is preferred when data sets are small, and NoSQL is preferred when data sets are large.
Yes, it is possible to use both SQL and NoSQL databases in the same application. This is known as a polyglot persistence architecture, where different types of databases are used for different parts of the application.
Yes, data can be migrated between SQL and NoSQL databases using various tools and techniques. However, the process may not be straightforward, and may require some manual effort.
Abhishek Ghosh
