Data is everything. Right from identifying patterns to categorizing/ grouping certain entities, data, or, more specifically, relevant data, is pivotal for the success of any business. For example, a customer’s demographic data allows you to fine-tune your marketing strategy, while page analytics grants insight into a website page visitor’s online behavior. However, unless the data is collected, stored, and managed in the correct way, you run into the risk of having data duplication, incomplete or partial data being presented, or data corruption from overwriting.
Hence it is crucial to have the correct database management service (DBMS) in place when building 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?
Database Management System can be considered an interface between a user and the central database (where the data is stored). The user can store, retrieve, and run queries on data using a DBMS. You can consider a DBMS to be like a virtual librarian who provides specific information from an organized shelf based on your query. Compared to a standard file system, a DBMS helps provide enhanced data security & integrity, concurrency, and a 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
- Simpler data search and retrieval
- Facilitates Quicker 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 interrelated databases distributed over a network managed by a central application)
- Hierarchical database management system (System organizes the data in a tree-like hierarchical structure, and the storage is made top-down or bottom-up format.)
- Network database management system (Complex model where the system can access each data through several paths.)
- Relational database management system (The data is stored in a tabular form, i.e., in rows and columns. Very user-friendly and highly scalable & flexible)
- Object-oriented database management system (System stores the 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 both has been a discussion for a long time. Each has its benefits and drawbacks, and you should choose based on your requirement.
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 table rows and column methods to store the data and supports 50 million rows or more in a table. Whenever someone wishes to retrieve 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 restructuring the database. This can be an expensive affair considering the size of the database. Moreover, the database must be spread through many computers, which may be challenging to handle at times.
What is MongoDB
On the other hand, MongoDB uses a different approach for handling data. Instead of storing the data in rows and columns of a table, MongoDB stores them in the form of JSON-like documents with arrays and nested documents. The fields in each document are different from each other. Hence, it becomes an effective solution for handling massive databases (hence the name “Mongo.”) So developers find it to be easier to adopt and use.
The limitation of MongoDB is that key-value pairs may affect data redundancy sometimes, which can cause excess usage of memory. Moreover, the size limit for a database is 16MB, and sometimes complex transactions can get complicated when ACID is not followed strictly.
Key Difference between MySQL and MongoDB?
MySQL follows a specific schema that defines the structure of the database. So all the columns and rows should follow a similar structure. Hence, flexibility in terms of data storage is limited, which can hinder the app deployment process.
MongoDB stores data in JSON-type documents with independent structures and is free from the restrictive schema. So the app deployment is comparatively higher.
While both support indexes for data search, the difference lies in searching for lost or non-defined indexes. In MySQL, the entire table is scanned for the relevant rows. MongoDB searches every document in the grouped collection for near-matching queries.
Overall Speed and Performance
In MySQL, the data is fetched after scanning multiple rows for extensive volume information. This takes time and causes the app to work slowly.
Since the application has to scan from individual documents and can handle multiple scans through unstructured data, it can be read and written in a single place and help the application work faster.
MySQL is written in C and C++ languages and works with multiple languages such as PHP, PERL, C, C++, JAVA, etc. Hence, developers can create applications that run for Windows, NetBSD, Linux, and IRIX binaries.
MySQL supports master-slave and master-master replication. Hence, with multi-source replication, MySQL can replicate multiple masters in parallel.
Using MongoDB, developers can set a secondary database that takes over if the primary fails. Moreover, MongoDB supports horizontal scaling using sharding which MySQL does not support.
MySQL provides a privilege-based security model that allows specifying clients’ roles when it comes to accessing specific data. However, the client will not know the reason for the denied access. Moreover, using SQL injection, the security can be bypassed, which makes MySQL a less secure environment.
You can offer role-based access with authorization, auditing, and authentication features using MongoDB. The database also supports TLS, i.e., transport layer security, and SSL, i.e., secure sockets layer for encryption using variable sets of privileges.
MySQL supports vertical scalability, which means the load on a single server can be increased by expanding its RAM or any other hardware configurations.
MongoDB, on the other hand, can be scaled horizontally using sharding. So system admins can expand the storage on the fly.
Both database systems have their own use cases and should be chosen over the other based on the application.
When to opt for MySQL?
- When pricing is a concern
- Small to medium-sized business with a small database
- Fixed Schema
- High transaction rate
When to opt for MongoDB?
- High data availability requirement
- Database with unstable schema
- Cloud-based opportunities
- Scalable Data
- Quick application building
MySQL is frequently chosen because of its ease of use and versatility in terms of administration. It promotes dependable data management strategies that might help your company through challenging times. If the data you’re working with is unstructured and complicated, though, MongoDB is the way to go. MongoDB should also be your first pick if you need to store massive amounts of data. It’s vital to remember that the decision between the two is mostly based on your business needs. Try our Database Services.