For years, relational databases were leading the market and the option was very apparent at that time, that is, either MySQL, Oracle or MS SQL. They have served as the basis for thousands of enterprise applications, though digital apps need more versatility and usability. Non-relational databases such as MongoDB has proven to fulfill the current requirements while replacing the current relational setting.
We are going to discuss MongoDB vs MySQL in this article. For organizations across the world that need a relational database, MySQL is becoming an affordable choice. Non-relational databases such as MongoDB, however, have emerged to meet the modern needs of our fluid data as the range and amount of data has risen significantly.
Let us start by learning about each one of the databases individually before diving into the comparison.
What is MongoDB?
MongoDB is a renowned document-oriented open-source database created by 10gen, currently known as MongoDB Inc. Here, the documents are generated and kept in BSON files, Binary JSON format, making it support all JS types of data.
Apart from that, MongoDB is also used for projects that use Node.js. In addition, JSON makes the use of a human-readable format to transfer data between servers and web apps. In terms of storage capacity and speed, it is also a good choice, as it provides better performance and effectiveness.
One of the top advantages provided by MongoDB is the use of dynamic schemas, such as fields or value types, that remove the need to pre-define the structure. This model facilitates the portrayal of hierarchical relationships, array storage, and the power to alter the structure of records by simply adding or removing fields. This NoSQL solution for improved scalability and high reliability deals with embedding, auto-sharding, and onboard replication.
What is MySQL?
MySQL is an open-source Relational Database Management System (RDBMS) that operates mainly on the relational database model. It makes the management of databases simpler and more versatile. MYSQL’s source code is available under the GNU GPL and Oracle Corporation owns and maintains the project. You have to pre-define your database schema in MySQL centered on your specifications and establish rules that help you regulate the relationships in your tables between fields.
It collects data in tables that are grouped into a database and makes use of Structured Query Language (SQL) to access data and commands such as ‘SELECT’, ‘UPDATE’, ‘INSERT’ and ‘DELETE’ to handle it,. Similar data can be stored in multiple tables, and you can conduct queries across different tables and minimize the risk of data replication by using the JOIN operation.
MongoDB vs MySQL- The Features
Features of MongoDB
- MongoDB offers an aggregation feature to use it in an efficient manner.
- MongoDB uses BSON (Binary JSON) format.
- MongoDB has come up with the Sharding feature.
- It can be used as a file system with load balancing and data replication features
- MongoDB supports field, range queries, regular expression searches.
- MongoDB is a schema-less database (written in C++) which makes it flexible.
- Indexes are built to enhance the performance of searches.
- It has MongoDB Management Service, a web tool that enables tracking of databases and machines and backs up the data.
- MongoDB supports multiple storage engines, such as WiredTiger Storage Engine and MMAPv1 Storage Engine.
- MongoDB has a rich Query Language, supporting all the major CRUD operations.
Features of MySQL
- MySQL is a relational database system.
- MySQL follows the working of a client/server architecture.
- It holds the ACID property and also allows distributed multi-version support.
- MySQL runs high-speed master/slave replication configurations and it offers cluster servers.
- It can be used on any platform and provides 24*7 support for open source and enterprise edition.
- MySQL is easy and absolutely free to use.
- MySQL has a solid data security layer that protects sensitive data from intruders.
- MySQL is compatible to run on many operating systems, like Novell NetWare, Windows, Linux, many varieties of UNIX.
- Its efficiency is high since it has a very low memory leakage problem.
- MySQL enables transactions to be rolled back, commit, and crash recovery.
Read Also | Most Common SQL Questions & Answers
MongoDB vs MySQL- The Comparison
Speed & Efficiency
The ability to manage huge unstructured data is a key advantage MongoDB has over MySQL. It is inherently quicker because it helps users to query in a particular way that is more workload-sensitive.
Developers claim that when it comes to handling massive databases, MySQL is somewhat slower when compared to MongoDB. It is not able to deal with huge and unstructured quantities of data.
MongoDB is just supporting master-slave replication. To make multiple copies of the data, it utilizes replica sets. At any point along the way, each member of this replica set will be allocated a primary or secondary function.
Read/write is performed on primary replicas by default and then is made to replicate on secondary replicas.
Also Read |Sql Vs NoSql – Which Is Best For You?
Both master-slave and master-master replication are being supported by MySQL. Multi-source replication gives you the potential to replicate data from multiple masters in parallel. Uniformity is not too complicated in master-slave replication, since every bit of data has exactly one owing master.
Whereas in master-master replication, they can deliver anything you want with no single point of failure if you understand how to work around it.
Flexibility of Schema
The fact that there are no limitations on schema design is the greatest advantage to MongoDB. Within a collection, you may drop a few documents and it is not important for these documents to have any relations. The only limitation to this is the supporting data structures. You might need to consistently optimize the schema depending on how the application can access the data because of the lack of Joins and transactions.
However, you need to properly identify tables and columns before you can store something in MySQL, and every row in your table needs to have the same column. And because of this, if you pursue normalization, there’s not much room for flexibility in the way of storing data.
The unstructured query language is used by MongoDB. To create a query in JSON documents, you need to define a document with a property that you want the results to align with.
Usually, it is performed using a very extensive set of operators using JSON that are linked to each other. Each property is viewed by MongoDB as having an implied Boolean AND. Boolean OR queries are natively assisted, but to accomplish this, you must use a special operator ($or).
To interact with the database, MySQL uses the structured query language. It is also a very strong language, considering its simplicity, consisting primarily of two parts: data definition language and data manipulation language.
MongoDB sharding has the potential to divide a collection into sub-sets of data to store them through several shards. This helps the application to expand even more than the resource limits of a standalone server or replica set.
Also, to optimize the usage of storage space and seamlessly load balance queries, it can manage the distribution of data to any number of nodes. It also allows automatic failure and redundancy for users.
Unlike MongoDB, there is no standard sharding implementation for MySQL. Although MySQL provides two sharding methods, that is, MySQL Cluster – built-in Automatic sharding functionality and MySQL Fabric, official sharding framework, they are only sometimes deployed. The standard practice is to carry out your own sharding system just like Facebook did.
The decision of designing for the sharding key, schema adjustments, and mapping among sharing the key, shards, and physical servers must be made by database administrators. The incorrect decision of sharding key can lead to system inflexibility also making this decision kind of an important one.
MongoDB does not support JOIN. On the other hand, multi-dimensional forms of data such as arrays and even other documents are supported by MongoDB. Putting one document in the other one is called embedding.
The JOIN operations are one of the greatest things about MySQL. JOIN renders the relational database relational, to be explained is easy words. With the support of a single SELECT command, JOIN allows any individual to link data from two or more tables into a single query.
MongoDB makes use of role-based access control with a versatile range of privileges. Authentication, auditing, and authorization are among the security features in this database.
In addition, the use of Transport Layer Security and Secure Sockets Layer for encryption purposes can also be made to use here. It’ll make sure that only the intended users can access to read it.
MySQL utilizes a security model that is privilege based. This implies that it validates a user and provides it with user privileges on a specific database including ‘CREATE’, ‘SELECT’, ‘INSERT’, and much more.
Nevertheless, it fails to address why specific access is denied to a particular individual. Encrypted links between the clients and the server using SSL are used on the transport layer.
MongoDB vs MySQL- The Difference
Now that we have understood about both MongoDB and MySQL, let us have a look at the differences to get an even clear and precise picture of both the databases.
|It displays data as a collection of JSON documents.||It displays data in tables and rows.|
|It uses object querying.||It is a structured query language.|
|Less risk of attack due to its design.||The risk of SQL injection attacks is there.|
|It is an ideal option if you have structured and/or unstructured data with the potential for quick growth.||It is an ideal option if you have structured data and need a traditional relational database.|
|High availability, scalability, replication, and sharding are inbuilt.||No efficient replication and sharding are available.|
|MongoDB uses Collection, Document, Field, Embedded Document, Linking, etc.||MySQL uses Table, Row, Column, Joins, etc.|
Bottom Line- Which one to go for?
With its flexible and easy concepts, as well as the friendly and supportive community, MongoDB offers convenience to the users, while after Oracle’s acquisition, users claim to have experienced the complete opposite with MySQL. Another problem with the latter is the emphasis of the owner on the growth of MariaDB, along with the reluctance to acknowledge community patches and have a sustainability plan. These parameters have culminated in a grinding halt, but for many businesses worldwide, MySQL still proves to be their one-stop solution to all the database needs.
Comparing the speed of MongoDB vs MySQL, developers claim that MySQL has certain issues due to the massive data volumes and it also lacks speed, so it would be a better option for businesses with smaller databases and searching for a more general solution. Although this is one of MongoDB’s benefits over MySQL, it is the ability to work with large and unstructured volumes of data.
Can MongoDB replace MySQL?
MySQL, MS SQL, Oracle and Server are almost interchangeable with RDBMS, but MongoDB is a document-oriented, cross-platform, NoSQL database. At times, replacing MySQL with MongoDB might be a wise decision. It is a nimble database that, as apps progress, enables rapid changes in the cognitive framework.
What are the disadvantages of MongoDB?
The MongoDB NoSQL database has a few drawbacks. High memory is used by MongoDB for data storage. For document size, there is a cap, i.e. 16 mb. In MongoDB, transaction support does not exist.
What database does Facebook use?
Facebook was developed from the scratch using open source software. The site is written majorly in the PHP programming language and uses a MySQL database infrastructure.
Does MongoDB have schema?
Data in MongoDB has a flexible schema. Collections do not enforce document structure by default. This flexibility gives you data-modeling choices to match your application and its performance requirements.
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