Data is everything. From identifying patterns to categorizing / grouping certain entities, data or, more specifically, relevant data, is essential for the success of any business. For example, customer demographics allow you to refine your marketing strategy, while page analytics provides insight into the online behavior of a website page visitor. However, unless the data is collected, stored and managed correctly, you run the risk of having data duplication, incomplete or partial data presented, or overwrite data corruption.
It is therefore crucial to have the right database management service (DBMS) in place when creating an application. Understanding what a DBMS is, exploring the different DBMS variants available and the different use cases of each DBMS will help you choose the right one for your project.
What is a database management system?
The database management system can be thought of as an interface between a user and the central database (where data is stored). The user can store, retrieve and execute queries on data using a DBMS. You can think of a DBMS as a virtual librarian who provides specific information from a shelf organized according to your query. Compared to a standard file system, a DBMS can improve data security and integrity, concurrency, and robust backup. Some of the other benefits of investing in a DBMS are:
- Multi-user access
- Scalable solution
- Reduces data redundancy and inconsistency
- Easier file sharing capabilities
- Easier search and recovery of data
- Facilitates faster decision making
- Easy data migration
Types of database management systems
Depending on the data model, distribution methods and user numbers, the DBMS can be divided into five types:
- Distributed Database Management System (a set of logically interdependent databases distributed over a network managed by a central application)
- Hierarchical database management system (The system organizes the data in a hierarchical tree structure and the storage is done in top-down or bottom-up format.)
- Network database management system (Complex model where the system can access each data via several paths.)
- Relational Database Management System (Data is stored in tabular form, i.e. in rows and columns. Very user-friendly and highly scalable and flexible)
- Object oriented database management system (the system stores data in objects with members such as fields, properties and methods.)
MongoDB (Object Oriented Database Management System) and MySQL (Relational Database Management System) are two of the most popular DBMS. However, the choice between the two has been a debate for a long time. Each has its advantages and disadvantages, and you should choose according to your needs.
What is MySQL
MySQL is a relational database management system developed by MySQL AB and is an open source program. MySQL is a popular DBMS that works on many operating systems and languages including PHP, PERL, C, C ++, JAVA, etc. A relational database management system uses row and column methods to store data and supports 50 million or more rows in a table. Anytime someone wants to recover data from a MySQL database, an SQL query is deployed that joins multiple tables to generate a required data view.
The limitation of MySQL is that any new data type that is not mentioned in the existing table structure would require database restructuring. This can be a costly affair considering the size of the database. In addition, the database has to be spread over many computers, which can sometimes be difficult to manage.
What is MongoDB
On the other hand, MongoDB uses a different approach to data processing. Instead of storing data in the rows and columns of a table, MongoDB stores it as JSON type documents with tables and nested documents. The fields of each document are different from each other. Hence, it becomes an efficient solution to manage massive databases (hence the name “Mongo”). Developers therefore find it easier to adopt and use.
The limitation of MongoDB is that key-value pairs can sometimes affect data redundancy, which can lead to excessive memory usage. In addition, the size limit for a database is 16MB, and sometimes complex transactions can become complicated when ACID is not strictly followed.
Key difference between MySQL and MongoDB?
MySQL follows a specific scheme that defines the structure of the database. Thus, all columns and rows should follow a similar structure. Therefore, flexibility in terms of data storage is limited, which can hamper the application deployment process.
MongoDB stores data in JSON type documents with independent structures and is free from restrictive schema. The deployment of the application is therefore comparatively higher.
Although both support indexes for finding data, the difference is in finding lost or undefined indexes. In MySQL, the entire table is scanned for the relevant rows. MongoDB searches each document in the grouped collection for the closest queries.
Overall speed and performance
In MySQL, data is retrieved after analyzing multiple rows to get detailed volume information. It takes time and slows down the application.
Since the app needs to scan from individual documents and can handle multiple scans through unstructured data, it can be read and written in one place and help the app run faster.
MySQL is written in C and C ++ languages and works with several languages such as PHP, PERL, C, C ++, JAVA, etc. Therefore, developers can create applications that run for Windows, NetBSD, Linux, and IRIX binaries.
MySQL supports master-slave and master-master replication. Therefore, with multi-source replication, MySQL can replicate multiple masters in parallel.
Using MongoDB, developers can define a secondary database that takes over if the primary fails. Additionally, MongoDB supports horizontal scaling using sharding which MySQL does not support.
MySQL provides a privilege-based security model that allows the roles of clients to be specified when it comes to accessing specific data. However, the customer will not know the reason for the denial of access. Moreover, by using SQL injection, security can be bypassed, making MySQL less secure environment.
You can provide role-based access with authorization, auditing, and authentication features using MongoDB. The database also supports TLS, which is the transport layer security, and SSL, which is the secure sockets layer for encryption using bundles. privilege variables.
MySQL supports vertical scalability, which means that the load on a single server can be increased by increasing its RAM or any other hardware configuration.
MongoDB, on the other hand, can be scaled horizontally using sharding. So system administrators can expand storage on the fly.
Both database systems have their own use cases and should be chosen over the other depending on the application.
When to choose MySQL?
- When pricing is a concern
- Small and medium business with a small database
- Fixed pattern
- High transaction rate
When to choose MongoDB?
- High data availability requirement
- Database with unstable schema
- Cloud-based opportunities
- Evolving data
- Rapid application creation
MySQL is frequently chosen because of its ease of use and versatility in terms of administration. It promotes reliable data management strategies that could help your business through tough times. If the data you’re working with is unstructured and complicated, MongoDB is the way to go. MongoDB should also be your first choice if you need to store huge amounts of data. It is essential to remember that the decision between the two is primarily based on the needs of your business. Try our Database services.