MongoDB Vs MySQL: Which Database is preferable for your Business?
Most people google this query: MongoDB vs MySQL to find the difference and make right selection of database for the development of apps as selecting the database for latest apps has been a great challenge for businesses particularly after the arrival of different technologies that have been dominant in the recent past like PostgreSQL, MS SQL, and MySQL.
Among these, MySQL has always been a preferable option for many companies that need a relational database. However, with a growing variety and massive volumes of data, MongoDB, the non-relational database has emerged as the right solution for many enterprises and startup development.
Now, there is increased competition between MongoDB and MySQL. After knowing the significance of both databases, one can easily choose the right one. In this article, I will compare both the databases based on several factors that will provide you insights to decide which database is better.
What is MySQL?
It is an open-source relational database management system. Like other relational Database management systems, MySQL uses SQL (structured query language) to get the database’s access along with keeping data stored in tables. In MySQL, the user can pre-define the database scheme based on the need to create rules to run the relationship among all the relevant fields in the tables.
The transfer procedure is essential for making any changes in the schema which can negatively affect the performance of application significantly. Furthermore, it can push the database to the offline mode.
Some of the big names that use MySQL are given below:
- US Navy
What is MongoDB?
MongoDB is a popular non-relational database that was developed by MongoDB Inc. In this database management system, data is stored in the form known as BSON. The MongoDB query language is used to store related data for query access. The fields are different for each document and there is no need to declare the document structure to the systems.
It allows you to make changes to the required document without making any alterations to other documents. In MongoDB, there is no need to take the system to the offline mode. Moreover, data is controllable using schema validation. Check mongodb query examples for further details.
MongoDB’s document data model naturally maps the objects in the application mode that’s why developers find it simpler to master and utilize. It also allows people to store arrays without any hassles by representing the hierarchical associations.
MongoDB benefits include on-board replication and auto-sharding embedding that enhances availability and scalability.
MongoDB is used by many well-known organizations such as:
MongoDB vs MySQL:
Let’s communicate the structure of both databases i.e., MongoDB and MySQL. In MySQL, the data value is stored in tables with MySQL database structure while SQL is used to access them. Schema is used to define the database structure. The prime requirement of the schema is that the rows have the same structure inside the table. It also requires specific data types to represent their values.
On the other hand, in the MongoDB database, the data is stored in JSON-like documents that are available in varied structures. MongoDB query language is used to assess data sets. These data sets are stored together to boost the mongodb query speed.
There is no need to define any document structure for creating the documents as the database is schema-free.
Both the databases MySQL and MongoDB use indexes for finding data. However, when an index is not defined in MySQL index optimization, the database engines scan the entire table to find relevant rows while in MongoDB, when the index is not defined, then every document is scanned to find a match to the query statement for selection.
- MySQL database supports master-master duplication and master-slave duplication.
- It allows duplication of multiple masters in parallel with the multi-source replication.
- MongoDB supports auto-elections, built-in duplication, and sharding, that allows developers to set a secondary database using auto-elections while sharding allows horizontal scaling which is considered a bit tricky to implement with MySQL.
MongoDB vs MySQL offers:
Oracle offers lifetime support at three primary levels for MySQL which are given below:
Premier: Suited for 1.5 years old
Extended: Suited for 6-8 years old
Sustain: Suited for 9+ years old
Each level offers 24*7 tech support along with access to updates, maintenance release, bug fixes, and patches.
Whereas MongoDB provides enterprise-grade support, which is lifetime. This allows users to upgrade user-flexibility to a newer version at their own pace.
Speed and Performance:
MongoDB is capable of controlling large volumes of unrestricted data as compared to that of MySQL. It stores the entity data on a single document. In addition, it allows users to read and write data in one place.
If large volumes of data need to be used, MySQL is relatively slower as compared to MongoDB. MySQL is less efficient in dealing with high volumes of unstructured data as compared to MongoDB as the data is spread across multiple tables that need to be accessed for writing and reading the data.
Security features in MongoDB include auditing & authentication. It is feasible for users to use transport layer security (TLS) and secure sockets layer (SSL) for encryption of ends.
Moreover, it allows the documents to only be read by the intended clients. It is also capable of establishing control over variable sets of advantages. In MySQL, the security models used are based on advantage.
In terms of performance, MongoDB is more advantageous as compared to MySQL. MySQL uses a rigid table structure model which creates hurdles in app development.
On the other hand, MongoDB speeds up the development cycle almost 4 to 5 times by using the data that has the flexibility of the JSON documents.
MySQL, one of the most popular databases, supports atomic transactions, allowing you to perform various operations inside a transaction.
Whereas, MongoDB support multi-document transactions in its 4.0 version. This step made MongoDB a robust open-source database in the unstructured space. Although, there are some limitations to unstoppable operations. Even after all this, the database is still a massive boon for MongoDB developers.
MongoDB architecture is entirely developed on the distributed structure while MySQL is not built on the distributed system architecture. Distributed systems offer data localization with the assistance of duplicate sets and automatic sharding which also maintains an “always-on” availability. It makes it possible to make the data available globally when they are placed locally for governance and latency access.
When is MongoDB usage Appropriate?
There are various instances when the use of MongoDB is suitable.
- When high data availability is your priority along with automatic, fast, and instant data recovery.
- If you want to lower the cost of schema migration while working with an unstable schema.
- If your services are mostly cloud-based, MongoDB would come handy for your business
This architecture is powered by sharding, which goes with the horizontal scaling and agility offered via cloud computing.
When to Use MySQL?
According to MySQL update scenario, it can be useful in the following conditions:
- If you are just starting your business and you don’t need an extensive database
- If you have a data structure that is not going to change over the period.
- In addition, if you have a fixed schema.
- If your budget is low and you are looking for a top-notch performance
- If data security is your top priority.
MongoDB is a preferred option as it allows you to build applications much quicker. In addition, it is suitable for dealing with various types of data. It enables companies to achieve efficiency in application management.
MongoDB reduces the complexity and assists in the translation of objects in the relational tables. MongoDB allows adjusting the database schema as per your business needs.
Its scalability is greater than MySQL. It can be scaled across platforms and within the multiple distributed data centers.
In terms of data volume, MongoDB can be scaled efficiently. On the other hand, according to MySQL update statement, the user has to carry out custom engineering tasks to achieve scaling. That is why many companies have already shifted from MySQL to MongoDB.
I hope this article will help you in making the right choice between MongoDB and MySQL. You can also check mongodb tutorials for more clarification. If you still have queries, you can contact our MySQL and MongoDB developers team to get proper guidance for your project.