SQL vs NoSQL: 7 Key Takeaways - KDnuggets

People assume that NoSQL is a counterpart to SQL. Instead, it’s a different type of database designed for use-cases where SQL is not ideal. The differences between the two are many, although some are so crucial that they define both databases at their cores.

Developers are all too aware of the need for continuing education. Whether there’s a new framework to pick up or a new service to learn, innovation and adaptation are fundamental to development. One of the hottest topics for today is the decision to go with the standard SQL database or to move to a NoSQL database.

NoSQL databases have been around for decades, thanks to the innovation of Carlo Strozzi. However, these databases weren’t in the news much until the early 2000s’. At this time, companies like Google and Amazon began putting more effort into developing NoSQL databases. Despite their recent popularity, many developers, architects, and designers may not be fully up to date with what NoSQL databases offer.

Thus, for a rundown on the differences between the two databases, check out the following 7 key takeaways that every developer should know.

  SQL databases are classified due to their use of the SQL language. Any database that someone can interact with via SQL is an SQL database. As a powerful, universally used language, it’s used across numerous databases such as Microsoft SQL Server, MySQL, PostgreSQL, and more. The query language allows users to write complex queries, pull data from several tables, and more. This universality makes it a safe choice for anybody who needs reliability.

On the other hand, although quite broadly classified, databases that do not utilize SQL are NoSQL databases. As we’ll soon see, the way to interact with NoSQL databases can greatly differ from one database to the next depending upon the schema design.

2. Relational vs Non-Relational   Other common names for the two databases in question are relational and non-relational databases. SQL or relational databases store data in predefined models that make them simple to use and rely upon. This model allows data to be inserted, updated, and extracted efficiently. What’s more, separate data sets can be related by unique identifiers—keys. In short, relational databases can be understood by all. Conversely, non-relational databases, NoSQL databases, are much more flexible in terms of data storage. While this may seem convenient, seasoned developers will understand the potential impacts of it. Over time, as more and more data is stored in a non-relational database, it may get difficult to keep everything straight as there are no standard models to follow.

  Piggybacking off the relational and non-relational aspect of databases, the differences in data storage is stark between the two styles.

SQL databases utilize schemas and tables which are predefined and easy to access for all users. You have your primary keys, fields, and values. From there, you can create as many tables as you’d like. You can insert secondary keys into tables and create complex relationships between several tables. This style of data storage makes it easy and quick to analyze large amounts of data together.

On the other side of the coin, non-relational databases allow you to create databases with dynamic schemas. You don’t need to create database models upfront. As you expand your database, you can add new models and mix data types seamlessly.

  SQL databases utilize tables, whereas NoSQL databases utilize just about anything else. The table-based approach goes hand-in-hand with the rigid schemas. You create as many tables as you need for your project, and you relate them with one another. Thus, you know exactly how a table will look when you need to examine data you haven’t seen yet.

NoSQL databases are quite vague in this sense, as their data is fluidly structured. There is no exact basis on which NoSQL databases are founded. Some popular NoSQL databases use graph stores, key-value pairs, wide-column stores, or document-oriented stores. The advantage of using NoSQL databases is that you have unlimited flexibility. You can choose whatever kind of database engine you want.

  One of the leading reasons NoSQL databases grew in popularity was due to their horizontal scalability. SQL databases require vertical scaling— you have to add more power to improve performance and capacity. In theory, SQL databases have an upper limit which can be reached when no more hardware improvements can be made. This may lead to extensive downtime and greater expenses in adjusting your model.

No longer do you have to invest money in more expensive components and higher-end CPUs to accommodate scaling an SQL database. When you use a non-relational database, all you need to do is add more machines to your arsenal. What’s more, horizontal scaling essentially provides redundancy as you have several machines and not one point of failure.

  If you have a solid grasp of your project and the data you need to store, deciding between an SQL and NoSQL database is straightforward.

When you have data that looks like it is inherently relative, use an SQL database. They’re reliable, easily accessible with SQL, and proven stores of data.

On the other hand, if your data is flexible and doesn’t have rigid relations, give a NoSQL database a shot. You have several popular providers to select from. You’ll find the fluidity in being able to define new schemas on the fly attractive. Plus, if you’re worried about future scalability, NoSQL databases are right for you.

  The last key takeaway to be aware of is the support for the two types of databases. SQL databases are giants—they have swaths of users around the globe. They’re well-established and come with thorough documentation. If you run into a problem with an SQL database, you’ll have plenty of help. Plus, there’s plenty of walkthroughs and SQL cheat sheets to help newcomers.

Although NoSQL has gained a following and popularity, they still lack the same support compared to SQL databases. You may struggle to find quality educational materials, support docs, and more.

  In short, if you know how your data looks, and what the future holds for your database, it’s easy to choose a type of database. SQL databases provide proven results, a powerful query language, and consistency. NoSQL databases are innovative, adaptable, and powerful databases that will only grow with time.

    Alex Williams is a seasoned full-stack developer and the owner of Hosting Data UK. After graduating from the University of London, majoring in IT, Alex worked as a developer leading various projects for clients from all over the world for almost 10 years. Recently, Alex switched to being an independent IT consultant and started his own blog. There, he explores web development, data management, digital marketing, and solutions for online business owners just starting out.