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Every business needs a well-designed database to manage the underlying functionality of their projects. Finding a well-organized, functional system allows the team to perform data-related tasks with ease which is eventually crucial to the success of the business.
There are numerous tools, databases, frameworks, programming languages, platforms, and operating systems to help the organization manage its data, and finding the right one can be a daunting task. Here is a comparative study on MongoDB vs. MySQL to ease out the research work a bit:
It is a widely prevalent language to communicate and manage database, constituting the database management system. Basic operations include: creating, inserting, updating, deleting and storing/managing relational databases. It is being used by top companies like LinkedIn, Google, YouTube, PayPal, Pinterest, Netflix, NASA, Walmart, US Navy, and Twitter and many more. This is an open-source relational database, which is very easy to use. Its syntax matches with that of SQL Server and it is already included in several popular web applications like Word Press.
MongoDB is a database management system that works across platforms. It is classified under the category of a NoSQL database program and makes use of JSON-like documents with the schema. It is being used by many famous organizations including Klout, Citrix, Zendesk, Twitter, T-Mobile, Hootsuite, Sony, MuleSoft, SurveyMonkey, InVision and Foursquare. Industries Production, big data, data science, finance, etc.
| MongoDB | MySQL |
| Flexible Schema | Structured Data |
| Scalability | ACID Compliance |
| High Availability | Replication |
| Document-Oriented | Indexing |
| Aggregation | SQL Queries |
MongoDB:
MySQL:
Both databases support rich query languages. MySQL makes use of structured query language while MongoDB makes use of MongoDB query language (MQL) that is designed for easy use of developers. Here is a succinct comparison between MQL and SQL syntax for common database operations:
| Difference Points | MySQL | MongoDB |
|---|---|---|
| What is the database structure? |
|
|
| Storing Records | All records are stored in rows and columns within tables of the database. | In MongoDB, each record is stored in the form of ‘documents’ instead of tables. |
| How is a table/collection stored in the database? | A table can be used to store related data types. | Documents belonging to a particular class or group as stored in as ‘collection’ like a collection of users or collection of customers or a collection of vendors etc. |
| SQL or No SQL | MySQL is a structured query language database management system that makes use of standard queries like insert, update, update, delete, drop, etc. | MongoDB is a NoSQL database that does not work on standard query structure. Different documents can be used in a collection to form a dynamic schema. |
| Are indexes needed? | All the tables within the database are scanned by the database engine in the absence of a proper index. | Every document within the collection is carefully scanned, providing a match to the query statement, in the absence of an index |
| More Salient Features | Joins can be used to reduce or remove duplication of data. | MongoDB makes use of replication and sharding to provide unique records. |
| Security Concerns | MySQL is often subject to SQL injection attacks, making it vulnerable. Encrypted databases operate on top of commodity DBMS so that even if the underlying system is compromised the attack is not able to obtain the data. But partial information in the form of plaintext is often leaked. | MongoDB makes use of object querying, where documents are passed to explain what is being queried. This method reduces the risk of attack as MongoDB doesn’t have a language to parse. There is no leakage. |
| Where and how are these databases deployed? | MySQL is written in C++ and C and has binaries for the following systems: Microsoft Windows, Linux, BSDi, AIX, FreeBSD, OS X, HP-UX, NetBSD, IRIX, and more. | MongoDB is written in C++, C, and JavaScript and has binaries for the following systems: OS X, Linux, Solaris, and Windows. |
| What types of replication/ clustering are available? | MySQL supports master-slave structure making use of multisource replication allowing working of several masters to be connected with one slave. | MongoDB has built-in replication, sharding, and auto-elections that helps setting up of backup database automatically in case the primary database fails. Sharding allows for horizontal scaling, which is difficult to implement in MySQL, by making use of replica sets to create multiple copies of the data. |
| Who’s currently behind the databases? | MySQL was founded by the Finnish/Swedish company MySQL AB. | 10gen started developing MongoDB in 2007 and has currently become a popular NoSQL database. 10gen was later renamed MongoDB, Inc. |
| Who provides support? | MySQL offers Oracle Lifetime Support at three levels: Premier for versions 1 – 5 years, Extended for versions 6 – 8 years, and sustainable for those who wish to make use of the same version for 9+ years. Each level offers 24 x 7 support with the knowledge base, maintenance releases, bug fixes, patches, and updates. | MongoDB offers Enterprise-Grade Support that gives you 24 x 7 support as well as an extended lifecycle support add-on, which allows you the flexibility to upgrade to newer versions at your own pace. Support for MongoDB gives you unlimited access to support, security fixes, updates, and more. |
| Who supplies ongoing development? | Ongoing development is done by the Oracle Corporation. | Ongoing development is done by MongoDB, Inc. |
| Who maintains the documentation? | The MySQL documentation is maintained by the Oracle Corporation and can be found at dev.mysql.com/¬doc | The MongoDB documentation is maintained by MongoDB, Inc. and can be found at https://docs.MongoDB.com |
| Which database should you use for your business? | There are many use cases for a relational database like MySQL. Any type of application that requires multi-row transactions such as an accounting system, would be better suited for a relational database. | Variety of use cases where MongoDB is well-suited include real-time analytics, content management, the internet of things, mobile. |
| Risk | It has the risk of SQL injection attacks. | Less risk of attacks due to design. |
| Analysis | It can be a great choice in case the data is structured and there is a need for a traditional relational database. | It is suitable in case the database (structured/unstructured) has the potential to scale rapidly in the future. |
| Data Structure | It has structured data with a clear schema. | It does not require any schema definition. |
| When not to use it? | MySQL is fine for read-only or read-mostly scenarios but more advanced multi-version concurrency control capabilities of Oracle, PostgreSQL, MS SQL Server, etc. | One might not want to use MongoDB while designing a core-banking system for a bank due to its non-compliance with ACID properties. It also does not have a provision for stored procedures. So if portability is required Internal Data Access API should be used. |
MongoDB stores data in the form of JSON like documents making use of MongoDB query language (MQL) for access. Every field will be unique and will differ across documents. Schema validation can be used to enforce data governance controls over each collection.
Image Source: https://enlyft.com/tech/products/mongodb
Various industry niches that have absorbed MongoDB in their development portfolio are Computer Software, Information Technology and Services, Internet, Marketing and Advertising, Hospital & Health Care, Financial Services, Higher Education, Computer Hardware, Telecommunications and Retail and many more.
MySQL is a relational database management system (RDBMS) from Oracle Corporation storing data in tables. It can be used to access data in an application, merge multiple tables in a process called a join.
The database schema is predefined with set rules to govern the relationships between fields in the tables of the database.
| MongoDB | MySQL |
| AI Applications | Web Applications |
| Edge Computing | Data Warehousing |
| Big Data Applications | Content Management Systems |
| Modern Serverless Applications | Social Media and Content Platforms |
| IoT Applications | Embedded Systems |
| Mobile Applications | Telecommunications and Healthcare Industries |
Both MySQL and MongoDB have their strengths and weaknesses. So if there is a requirement where the data is required to have multi-row transactions or have to support a legacy application, a relational database may be the right choice for the business organization. But if a more flexible and schema-free solution is required to work with unstructured data, then MongoDB will be preferable.
The performance of MongoDB is improved over MySQL as MongoDB does not make use of joins to connect data, improving performance. Regardless of which one you select, MySQL vs MongoDB can be used to create single data management that connects your MySQL, MongoDB, Cloud and more such solutions without the need to code. Konstant Infosolutions help serves business communities with relevant projects acknowledging them as outstanding by others in their field. If there is a need to requisition some evidence you may request a free quote. We will be happy to assist!
Manish Jain is the co-founder and Managing Director at Konstant Infosolutions. He is responsible for the overall operations of the company and has played a major role in bringing Konstant up from its humble beginnings and, with his immense energy and drive, transforming it into a globally trusted name in IT solutions.
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