MongoDB Vs MySQL: The Differences Explained

MongoDB Vs MySQL: The Differences Explained

First of all, a big thanks to technology which makes us capable to express something in front of the world. And now, without further ado, let’s get down to our topic. This time, the topic of discussion is database management systems in the tech marketplace. If goes by the number, there are many database management systems to choose from. But without going inside all those are available, we will discuss the most dominant ones. MongoDB and MySQL.

However, there was a time when the obvious choices were MySQL, Oracle or MS SQL, to mention a few. But with the change in demand and demand for more scalability and diversity, the option of MongoDB emerged with a big fanfare.   

For now, it is between MongoDB and MySQL, and this write-up will take you deep down in every aspect where you can compare which database is better for your organization. 

Let’s start with the basics

We will explore MongoDB vs MySQL. MySQL has become an inexpensive option for organizations around the globe that need a relational database. However, as the variety and volume of data has increased in recent years, non-relational databases like MongoDB have arisen to meet the new needs of our fluid data.

Who Uses These Databases?

Both of the databases are popular throughout the world. That’s why many organizations using both of them. 

MySQL: It has a large following until now since 1995. Organizations that use MySQL include—Pinterest, Twitter, YouTube, Netflix, Spotify, NASA, Paypal, and Walmart. 

MongoDB: It was released later in 2009, but still is used prominently in organizations including Klout, Citrix, T-Mobile, Twitter, MuleSoft, FourSquare, and InVision.

Querying Language

MongoDB uses an unstructured query language. To build a query in JSON documents, you need to specify a document with properties you wish the results to match. It is using a very rich set of operators that are linked to each other using JSON. As a database, MongoDB treats each property as having an implicit boolean AND. 

On the other hand, MySQL used the structured query language SQL to communicate with the database. It is a simple and very powerful language that consists mainly of two parts: Data definition language and data manipulation language (DML).

What About Database Structure?

MySQL: MySQL stores data in tables and uses the structured query language (SQL) for accessing the data. To define database structure, it uses schema and requires that all rows within a table have the same structure. 

MongoDB: Unlike SQL, in MongoDB data is stored in JSON-like documents in varied structures. It stores all the related data together and accesses it by using the MongoDB query language. 

Now here comes its USP. It is schema-free which allows creating documents without having to define the structure of the document first. And these documents can be easily changed by adding or deleting fields. 

And because the documents have a unique structure, new fields can be added at any time and contain any type of value.  

By using the MongoDB data model, one can represent hierarchical relationships, data arrays, and other complex structures in the database. In some cases, MongoDB performance is improved over MySQL because it does not use joins to connect data, improving performance.

Security Model

MongoDB uses role-based access control with some set of privileges. If we talk about its security feature, then it includes authentication, auditing, and authorization. For encryption purposes, developers can use Transport Layer Security (TLS) and Secure Sockets Layer (SSL). This encryption will ensure that the data is only readable and accessed by the intended client. 

On the other hand, MySQL used a privilege-based security model. This means it authenticates a user and facilitates it with user privileges on a particular database such as CREATE, SELECT, INSERT, UPDATE, and so on. But unlike MongoDB, it unable to explain why a given user is denied specific access. On the layer of transport, it uses encrypted connections between clients and the server using SSL. 

Where (And How) Are These Databases Deployed?

MySQL: It is written in C and C++ and has binaries in the following systems such as—Linux, OS X, Microsoft Windows, AIX, FreeBSD, HP-UX, IRIX, NetBSD, and more.

MongoDB: It is written in C++, C, and JavaScript and has binaries for the following systems: Linux, OS X, Solaris, and Windows. 

Support

MySQL: it is known for offering Oracle Lifetime Support at three levels. It goes like this—

  • Extended for versions 6 – 8 years old
  • Premier for versions 1 – 5 years old
  • Sustain for those who have been using the same version for 9+years.

Amazingly, each level has 24×7 support with the knowledge base, maintenance releases, bug fixes, and updates

MongoDB: It offers Enterprise-Grade Support that extends beyond break/fix. It also comes with 24×7 support and an add-on of extended lifecycle support. It is flexible enough to allow you to upgrade to new versions. Unlike MySQL, the support for MongoDB gives you unlimited access to support, security fixes, and more

Performance and Speed

MongoDB has an edge over MySQL when it comes to the ability to handle large unstructured data. The former one also allows users to query in a different manner that is more sensitive to workload. 

As per developers, MySQL is also slower than MongoDB when it comes to dealing with large databases, as it is unable to cope up with the large and unstructured amounts of data. 

Developers note that MySQL is quite slow in comparison to MongoDB when it comes to dealing with large databases. It is unable to cope with large and unstructured amounts of data.

Conclusion

Now, it comes to our moot point of discussion. Which is better MongoDB or MySQL? Actually, for this, you need to take into consideration your project goals and many other things. 

On one hand, MySQL is known for its high performance, reliable data protection, and comes with an ease of managing data. Proper data indexing with it can resolve your issue with performance, facilitate interaction and ensure robustness. But here comes its limitation. If your data is not structured and complex to handle. Or if predefining your schema is not easy for you, you should opt for MongoDB.  

And if you want to handle a large amount of data and want to store it as documents, MongoDB is here to serve you. So here, one is not necessarily better than the other. MongoDB and MySQL will both here to stay. 

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