MongoDB vs MySQL: Let’s end the debate today!
Are you planning to build a mobile app? Or, you want to integrate some brand-new features in your existing app? Well, for both situations, selecting the right database can be a little complex.
The database is the heart of an application. It keeps the user’s data organized and makes it accessible at the right time and in the proper context. If you are planning to develop a mobile app and your goal is to get millions of app users – your choice of the database should be a well-researched decision.
Let’s suppose that you have developed a world-class class mobile application and you are getting an ever-increasing number of new users. However, if your backend isn’t powerful enough to handle such traffic, your application would crash and will cause a service meltdown.
This is the reason why you have to focus on the decision of the database while building a mobile application. If your database isn’t structured or set up effectively, it will end up being a gigantic problem for you in the long run.
So, understand what every database has to offer and then decide the one that’s perfect for your app development project. To help you out, we will be comparing the two most popular databases today – MongoDB and MySQL. So, let’s get started.
|2||Database Type||SQL, RDBMS||NoSQL, Document-Oriented|
|Stores Data in Rows and Columns||Stores Data in Documents|
|3||Speed and Performance||It is a Bit Slower and Can’t Handle Unstructured Data||It is Faster and Provides Better Performance|
|5||Scalability||Vertically Scalable – By Increasing RAM||Horizontally Scalable – By Adding More Servers|
|Scaling is Tough with MySQL||Scaling is Easy with MongoDB|
|6||For High Availability & Cloud Support||Provides Better Handling Techniques For Stable Environments||Provides Improved Handling Techniques For UnStable Environments|
|Not Recommended for Cloud-Based Storage||Recommended for Cloud-Based Storage|
|7||CAP Theorem||Opts for Consistency & Availability||Opts for Consistency & Partition Tolerance|
|9||Deployment & Community Suppor||Excellent and Helpful||Good and Helpful|
|10||Best Used For||Legacy Apps or Apps that Need Multi-Row Transactions||Real-Time Analytics, IOT and CMS Apps|
MySQL: MySQL stores the data in tables and utilizes the SQL – Structured Query Language – to access it. It follows schemas to define the database structure, requiring that all rows and columns inside a table have a similar structure with values being represented by a particular data type.
Because of the same, there isn’t much room for flexibility in the way of storing in MySQL. As a result, the app deployment process becomes too slow because of the fact that even a little change in data model demands for the change in schema design as well. Here is how it stores data:
As you can see, the table structuring is quite rigid and it isn’t effectively alterable. You can’t even type letters where numbers are expected. So, it is a bit complex when it comes to flexibility.
MongoDB: In MongoDB, the user’s information is stored in JSON-like documents that can have variable structures. To improve the query speed, related data can be stored together in MongoDB, which can be accessed by using its query language. MongoDB lets you create documents without defining the structure as it is schema-free. These documents can be modified easily without deleting or adding fields.
In MongoDB, documents can have different structures. New fields can be added whenever required and they can store any type of value. This key distinction is a major advantage to the developers as the code defines the schema and you don’t need to experience schema migration any longer.
My SQL: As mentioned in the above point, MySQL stores data in rows and columns. That means multiple tables have to be accessed for accessing it. This slows down the speed of application and hence decreases its performance. Also, MySQL is very slow compared to MongoDB when it comes to managing large databases.
Hence, it is a superior choice for apps that need to handle small data volume and is searching for a general solution as it can’t adapt to large and unstructured data types.
MongoDB: One of the best advantages of MongoDB is that the data for an entity in it gets stored in a single document. This makes the app faster. It also allows writing and reading data all in one place. The other advantage of MongoDB is its capacity to handle unstructured data in large volumes. It is faster than MySql.
MySQL: It utilizes SQL to communicate with the database. Regardless of its simplicity, it is surely an incredible language which comprises mostly of two parts: DDL (data definition language) and DML (data manipulation language).
MongoDB: It utilizes an unstructured query language. To create a query in the JSON document, you have to specify a document with properties you wish the outcomes to match. It is commonly executed utilizing an exceptionally rich set of operators that are connected to one another utilizing JSON.
MySQL: MySQL uses a privilege-based security model. This implies that it validates a user and facilitates it with user benefits on a specific database, using queries like SELECT, CREATE, INSERT, UPDATE, etc.
However, it fails to clarify why a given user is denied explicit access. On the transport layer, it utilizes encoded connections among customers and the server using the SSL. While using MySQL, the risk of SQL injection is always there due to which it is considered less secure as compared with MongoDB.
MongoDB: It uses a role-based access control with a flexible set of benefits. Its security features include authorization, authentication, and auditing.
Additionally, it is also possible to utilize Transport Layer Security TLS and Secure Sockets Layer SSL for encryption with MongoDB. This guarantees it is just open and readable by the authorized users.
MySQL: In numerous situations, most of the SQL databases like MySQL DB, SQL Servers, Oracle, are vertically scalable, which implies that you can increase the load on a solitary server by expanding CPU specifications or RAM.
When compared with MongoDB, MySQL isn’t that good with regards to scaling. It was initially designed as a single-node system and not with the cutting-edge data center concept. The largest MySQL installation can’t scale by utilizing MySQL as a solitary framework and must depend on sharding, or splitting a data index over various instances and nodes.
Also, most sharding solutions in MySQL are manual and make application code complex. Any performance gain is lost when queries access information over numerous shards.
MongoDB: NoSQL databases are horizontally scalable. An advantage of horizontal scalability is that it can give system administrators the capacity to expand the storage on the fly, being just constrained by what number of machines can be connected effectively.
This means that you can handle more traffic with MongoDB by sharding or including more servers for your database and by making a MongoDB cluster with various servers/nodes.
It is like adding more flooring to a similar house instead of including more homes to the street. The MongoDB can in the end evolve and turn out to be increasingly predominant, making it the favored choice for big or ever-changing liquid fluid sets.
MySQL: For stable environments, MySQL database provides better handling techniques. Taking a backup of MySQL isn’t required, as it as of now has a replication provision integrated inside. But, setting up a master-slave is moderately slower compared with MongoDB.
MongoDB: For environments that are unstable, MongoDB offers an improved handling technique compared with MySQL DB. This is because it requires less time for the active secondary nodes to choose a new primary node if there should be an occurrence of failure or inaccessibility of primary nodes. In addition, due to built-in native replication, making a backup for a MongoDB database is fast and simple when compared to MySQL as it has built-in replication support.
Also, cloud-based applications require data to be equitably and effectively spread over various servers for scaling. MongoDB can load a high volume of data when compared to MySQL in a brief timeframe with an in-built sharding feature, and it is clear to segment and spread out data over various servers.
According to CAP theorem, it is impossible for a database to altogether provide more than two out of the following three assurances:
Now let’s see how MySQL and MongoDB work as per CAP theorem:
MongoDB: Under the CAP theorem, MongoDB provides Consistency and Partition tolerance (CP). This implies that the consistent view of the database will be accessible for every one of the users.
Despite the fact that the user of one node should wait for some other node to come to an agreement before having the option to write or read to the database. For this situation, the availability takes a lower priority in relation to consistency.
MySQL: As per CAP, MySQL database provides Consistency and Availability (CA). This implies that data will be consistent between all the nodes as long as entire nodes are online.
This will permit you to read/write from any node and be certain that the data is consistent. If at any time a partition in between the node is built up, the data will get out of synchronization and the problem will not be solved until the partition is settled.
When we talk about MongoDB vs MySQL depending on developer’s performance, it looks like MongoDB has a clear cut advantage. MySQL utilizes an inflexible table structure model which makes it slower for developers to make an application work seamlessly using it.
MongoDB accelerates the development cycle by around 4 times by only working with data that has the flexibility of the JSON reports. Along these lines, you can say that a developer’s productivity is higher when utilizing MongoDB.
MySQL: It is as of now owned and maintained by Oracle Corporation. It can be installed from the source code itself, manually.
It is also available for cloud, SaaS and Web applications and can run on different platforms including Linux, MacOS and Windows. One major advantage of MySQL is that it is in the industry for a long time and hence it has a stronger community.
MongoDB: It is as of now owned and maintained by MongoDB Inc. It is incredibly simple to deploy MongoDB. It is available for Cloud, SaaS and Web applications and can run on numerous platforms including Linux, MacOS and Windows.
Also, MongoDB has been seen to attract developers with its perfect and simple working along with its helping and collaborative community.
To conclude the above discussion, all we can say is – MySQL and MongoDB – both have their own pros and cons. And, to find out which one is best for you, you need to take into consideration your business goals and project requirements. Let’s see which one is suitable in which condition.
With this, we have now investigated everything that is required to get you at a position where you can choose which database would be better for your business. MySQL is generally used for its management ease and flexibility. Its proper data handling techniques can assist you to address various concerns.
However, if your data is perplexing and unstructured, or if you can’t define your schema ahead of time, you can go with MongoDB. Additionally, if you need to store a large volume of data, MongoDB should be your preferred choice.
If you still need assistance, you can connect with our experts right here.