The comparison between relational and non-relational databases is causing huge controversy in the technology space. Different individuals have their reasons for their choice of database. This indirect struggle for power between SQL and NoSQL can make it difficult for you to make a choice.
This article aims at making the decision of using either NoSQL or SQL easier for you. I remain very subjective as to which should be used in development, but you’ll find enough information here to help you make a choice.
Should you always use NoSQL instead of SQL? Yes, NoSQL is the right choice of the database system to be used. It is not restrictive in the choice of language as you’ll find with SQL. It is also designed for horizontal scalability which means it can handle more traffic by simply adding more servers rather than purchasing more compute power such as RAM or CPU.
As you proceed in reading this article, you’ll see reasons that validate this choice of using NoSQL rather than SQL.
In this article, you’ll benefit from the following discussions on NoSQL and SQL:
- Understanding SQL and NoSQL, with The Differences.
- When to Use Either of the Databases.
- NoSQL over SQL: A Case Scenario.
- Pros and Cons of SQL and NoSQL.
- Types of NoSQL Databases.
- Additional Information on NoSQL.
- Learning Resources for NoSQL.
To choose between the two database systems, you essentially need to know about them deeply. This will help give you a broader perspective of what they are and their differences. Without further ado, let’s examine what the two database systems are and their differences.
You may have some idea on what SQL and NoSQL databases are, however, to understand this article you don’t need to know a lot. At the very least, being aware of the fact that they are both some structure of a database is enough.
In simple terms, a database is where data and information are stored for manipulation. A database is required in any modern application regardless of what it does. There is usually a need to store information such as username, passwords, address, etc.
A schema is an important concept in databases, you’ll get to hear it a lot when working with databases. It is a blueprint as to how your database is to be structured i.e. it describes the characteristics of the information a database will store.
When you realize that databases aren’t just about storing data but also about retrieving them, it’ll be clearer how important it is to have a structured database. It is not a rare sight to see lots of programmers using SQL in their projects. But that is changing rapidly because NoSQL does a better job at structuring data.
Structured Query Language (SQL) commonly called Sequel or Es-kew-el is a programming language used in storing data in a relational database. It is the standard language for relational databases.
In brief, SQL stores data in tables. Since it stores data, it’s definitely also being used in retrieving the stored data. SQL does more than storing and retrieving data, but on a basic level—which is all you need for now—it’s fine to simply understand it to be a tool for working with data.
You’ll find a lot of techies referring to NoSQL as the modern SQL language. Well, it’s not far off from the truth. NoSQL helps to meet up with the modern methods of developing applications, taking into consideration the frequency at which data structures can change.
NoSQL does not enforce the use of relations between tables. NoSQL allows you store data in different formats such as JSON—which emphasizes storing data in columns, not rows. If allowing you store data in different formats isn’t massive enough, it also allows you to query and retrieve data using different methods such as HTTP or CLI.
Looking at SQL and NoSQL in this section, you’ll learn that both differ on various fronts. While you’ll get to see what those areas are and what differences both databases have, it’s fine to just link SQL to being Relational and NoSQL to being Non-Relational.
As you’ll notice soon, there are a ton of differences between SQL and NoSQL. But you’ll find it incredibly beneficial to know the major differences.
The top difference between both databases is the query language. SQL uses a specific query language also referred to as Structured Query Language to manipulate data. This special language for querying data is one of the reasons SQL is quite powerful.
However, the lack of flexibility that comes with it is also its downfall. SQL imposes a restriction on the method that can be used in querying data.
NoSQL, on the other hand, doesn’t have a specific language for querying data. While you may think of this to be a disadvantage, it provides a lot of benefits. Its lack of a query language allows data to be stored in different ways, most popular being the column-oriented or key-value method.
Since SQL has a restricted structure of storing data, it requires you to have a predefined schema before working with it. This approach to storing data is quite a rigorous process.
Keeping a focus on schema structure: unlike SQL, NoSQL has a feature for a flexible schema which allows you to work with a database without necessarily creating a predefined schema.
Wrapping this section up, you can conclude that the rigidity of SQL and the flexibility of NoSQL makes them very much different.
You’ll agree that making plans for future changes is the best way to go about doing things. This also applies to the comparison of SQL and NoSQL.
Looking at NoSQL, you’ll figure out that NoSQL is a better option when considering extensibility. Besides, flexibility is key to being able to make changes.
It is easier to scale a NoSQL database than it is to scale a SQL database. As a product experiences an increase in user base over time, NoSQL allows you to make changes to adjust to the increasing demand for services.
To adjust to the increasing demand for service, a software product has to scale. There are two ways of going about this: vertical scaling and horizontal scaling.
Vertical scaling is a means of scaling by increasing the computing power of your machine. Compute power varies. It can be CPU, RAM size, Storage size, etc.
Horizontal scaling is a means of scaling by adding more machines to your pool of machines. Instead of increasing the computing power of one machine, you’ll increase the number of machines.
As your application experiences more traffic, scaling horizontally is often a better choice than scaling vertically. This is the reason why you’ll see big companies having their own data centers with lots of machines.
Here’s where the databases come in: It is easier to scale NoSQL databases across many servers or machines i.e. horizontally than it is to scale SQL databases because SQL databases are not designed to scale horizontally. This doesn’t mean they can’t scale horizontally, but it can be quite challenging.
You’ll find that SQL has a larger user community than NoSQL. This is because SQL has been in use for a long time. It is difficult for people to make the switch to NoSQL databases.
However, it’s only a matter of time because things are changing gradually. There are growing NoSQL database communities out there. You’ll find a lot of people using the Oracle NoSQL database.
So, you shouldn’t be swayed by the larger community of SQL database users. While it means you’d easily find support from others, you can also get support from the growing NoSQL database community.
The points above are just some of the differences between SQL and NoSQL, there are many more differences.
Considering the sections above, you should have some knowledge of SQL and NoSQL databases at this point, so it’s fine to dive into the best use cases.
In this section, you’ll see the suitable cases where you should use the SQL or NoSQL database.
- When working with highly complex applications.
- When it’s certain that you won’t be working with a large volume of data.
- When working with complex queries or reports is a possibility.
- When scalability is not a concern.
- When a change in database schema is a possibility in the long run.
- When working with a large amount of data.
- When scalability is a concern.
- When you want flexibility in the database structure.
These short and brief details are the most common reasons to use either database.
Using an address book for this illustration, a user contact details can consist of the following:
Great, now, the issue here is that some of the users may have more than a single name, multiple telephone number, and address. The conventional way to do this to itemize all the additional data for each field and create a database for them, which is what you’ll do when using SQL.
In the long run, you can keep creating tables for all these extra details, but eventually, no matter how many tables you create now, some new data may show up to be added to the database.
To keep up with this, you may have to keep creating tables and it is very much inefficient. You can’t predict the number of users, their needs or make an assumption that they would not have extra details that you’ll need to save. Therefore, the rigidity that comes with SQL is a huge disadvantage.
For this reason, NoSQL is definitely a better alternative. A Non-Relational database stores all data about a user in a document which can be given any name and is usually in a JSON format. This flexibility in its schema makes it easy to add and remove data without stress.
In conclusion, for software products that imitate this kind of user behavior, a NoSQL database is the right choice.
SQL and NoSQL stand shoulder to shoulder. Without a doubt, they are both incredibly powerful databases. However, you’ll agree that everything has its advantages and disadvantages. No matter how good a technology is, you’ll realize that you need to consider the trade-offs.
In this section, you’ll see the advantages NoSQL has over SQL, vice versa. You’ll also see the disadvantages of both sides.
The following are some of the major advantages of using SQL relative to NoSQL:
- SQL is in compliance with a term commonly known as ACID, which stands for atomicity, consistency, isolation, and durability. This helps improve the integrity of your database and also makes recommendations on how you transact with your database.
- There is an active community of SQL developers, so you can easily find a solution to whatever problem you encounter when using SQL.
- SQL uses an industry standard querying language. This allows uniformity when working with SQL databases.
The following are some of the major disadvantages of using SQL relative to NoSQL:
- SQL compliance with ACID is a sacrifice made for processing speed and flexibility in operation.
- Scalability in SQL is not an easy process when compared to NoSQL, it requires more resources which are costly for an organization.
- SQL maintains a rigid schema, making it hard to have a dynamic and flexible database.
With the examination of the advantages of SQL, here also are the advantages of NoSQL:
- NoSQL is also designed to handle voluminous data within an organization and still maintain efficiency by operating faster than SQL.
- It is very dynamic, you can store any data set in a single document and can easily manipulate them when the need arises.
- Scalability in NoSQL is very easy and less costly compared to SQL. All you simply have to do is upgrade your servers.
- With NoSQL, you are not required to have a predefined database schema to begin working with.
- It works fine with frequent software changes.
- There are lots of options for NoSQL databases, you’re spoilt for choice.
Even Gold has its disadvantages, below are some of the disadvantages of NoSQL:
- The NoSQL user community is not as active as the SQL user community.
- Lack of tools to report performance to aid in validating your applications.
- NoSQL lacks standardization which implies that there is no specific database rather. There are different types such as MongoDB or CouchDB.
NoSQL does not have a specific database type as you’ll find with SQL. So, NoSQL databases take different forms, which include:
- Key-value stores: which is one of the simplest forms of storage such that it contains a key and value for the specified key.
- Document databases: which are more verbose when you compare them with key-value stores and can also store multiple key-value pairs.
- Wide-column stores: which you’ll find in use when dealing with a large amount of data.
- Graph stores: which are more suitable for storing information about a network.
As with all technologies, there will always be resources to learn from. However, getting your hands on quality tutorials can be a hassle. You don’t have to do that. In this section, you’ll get links to quality resources to help you learn NoSQL in no time.
If you believe at this point that NoSQL is important enough for you to learn, then you’ll find the resources below immensely useful.
The most popular types of NoSQL databases are MongoDB and Cassandra. So, here are resources to help you learn MongoDB and Cassandra:
- When working with anything new, and in this case Non-relational databases, the first thing to do is to look into the official documentation. You can read the documentation on MongoDB here.
- You can also get free online training when working with Cassandra from Cassandra tutorials as well.
The above are the two getting started resources you can dig into yourself. To get your hands dirty quick, this Udemy course will give you a complete guide to becoming a developer with skills in the MongoDB NoSQL database.
In this article, you’ve seen what databases are, where SQL and NoSQL come into the picture. Hopefully, you also understand what the differences exist between SQL and NoSQL as well as the benefits of implementing any of them.
If you already have knowledge of SQL, then NoSQL should be less difficult to learn. But if you have no previous knowledge of databases, it may be strange learning NoSQL. Regardless, it should not be difficult learning to use it either.
No matter where you fall—beginner to databases or not—the Udemy course on MongoDB will be quite valuable in making learning easier.
To wrap up the write-up, NoSQL is a better choice than SQL. Its flexibility is no doubt a reason to always use NoSQL. It’s a no brainer. Enjoy the flexibility, dynamism and scalability benefits that come with NoSQL and have fun managing user data.