MongoDB vs MySQL: The Clash Of Two Popular DBMS Titans
For any software application, the database is the fundamental backbone that must be managed effectively. And that can be done with good database management systems. A database management system is responsible for managing and retrieving all needed information from well-organized chunks of data.
Two popular names in the world of database services are MongoDB and MySQL. There has been a constant comparison between the two. MongoDB vs MySQL has been an interesting evaluation.
Though both these technologies, MongoDB or MySQL, focus on data extraction and report generation, they possess different designs and functionalities. Both have their own set of loyal developers who make the most of these database systems.
Before we compare them both, let us go through them individually with their set of features and benefits.
What Is MongoDB?
MongoDB is a popular, open-source NoSQL database that offers high productivity and performance for your data-driven applications. It is leveraged as an apt choice to the traditional RDBMS, especially when there are huge sets of data distributed everywhere.
It can easily manage, store, and retrieve document-based information. It stores data in documents with a flexible schema and not in tables like other RDBMS. It offers a developer-driven data platform and faster go-to-market time with the modernized database.
MongoDB is completely managed in the cloud with high-end scalability. It can be self-managed in any environment and can be executed from anywhere. It is a non-relational DBMS that supports transactional analytics through a common query interface and data model.
Good Read: Top 15 MongoDB Alternatives And Competitors
MongoDB Advantages:
- Simplistic installation and ease of use
- Completely cloud-based developer platform
- Cost-effective and flexible
- Strong query and analytical capabilities
- User-friendly design
- Fast speed and high accessibility
Sharding and scalability
MongoDB Features:
- Ad-hoc queries for enhanced, real-time analytics
- Appropriate indexing for better query results
- Replication for better data accessibility
- Load balancing
- Document-oriented and open-source database
- NoSQL database and dynamic schema
- Aggregation and high performance
Companies That Use MongoDB:
- Forbes
- Toyota
- Sanom
- Intuit
- Verizon
- Marsello
- Conrad
- TIM
- Helvetia
- eBay
- MetLife
- Shutterfly
- Adobe
- Barclays
- Bausch
- Comcast
- DHL
- HSBC
- KPMG
What Is MySQL?
MySQL is a leading relational database management system (RDBMS) that is free to use and open source in nature. It is meant for small and large applications. It makes optimum use of SQL for querying and operating database systems.
It helps in handling, storing, modifying, and storing data in a systematic manner. It helps developers in meeting the needs of the next-gen cloud, web, and other services with complete scalability and round-the-clock uptime.
MySQL is indeed simple to learn and hence considered a developer’s delight, especially for the development of web-based software applications. It is an Oracle-backed database that executes seamlessly on almost all platforms – Windows, Linux, UNIX.
Good Read: PostgreSQL vs MySQL: A Detailed And In-depth Comparison
Benefits Of MySQL:
- The lessened total cost of ownership
- Data security and open-source flexibility
- Comprehensive workflow control
- On-demand scalability with faster development
- Free to use and portable
- Stable, reliable, and powerful
- Round-the-clock uptime
Features Of MySQL:
- Support for huge databases
- Client and utility programs
- Secure and easy to use RDBMS
- Permits rollback
- High-end performance and productivity
- Dual password support
- Partitioning
Companies Using MySQL:
- Sony
- BBC
- NASA
- Bank of America
- YouTube
- Spotify
- Bayer
- Caterpillar
- GitHub
- Square
- Nokia
- Zappos
- Telenor
- US Navy
- Zendesk
- Sage
- Airbnb
- Braun
MySQL vs MongoDB – Similarities
- Database management systems
- Use a robust query language
- Enables data extraction
- Report generation
- Support for Java, Python, NodeJS, PHP
- Support to deliver, modify, or deploy cloud-native applications
- Open-source and free-to-use code
- Provide full-text search and indexing search through phrase and term search
- Offer data replication
- Storage of data on a computer system or network
MySQL vs MongoDB: Comparing Two Well-known Database Services
As we delve deeper into what the difference between MongoDB and MySQL is, here is a detailed evaluation chart that offers a peep into the basic variations in both.
| Parameters | MongoDB | MySQL |
| Overview | A non-relational database system presenting enhanced flexibility and horizontal scalability | A strong relational database system, presenting a common database environment for skilled IT experts |
| MongoDB Vs MySQL Performance | Follows a hierarchical data model and keeps data together, lessening the need for joins, optimized for write performance | Optimized for high performance joins with many tables that are indexed, optimized for high performance across many tables |
| Developed By | MongoDB Inc. | Oracle |
| Released In | 2009 | 1995 |
| Type of System | Non-relational or NoSQL system | Legacy system designed with SQL |
| Applications | Legacy business sites, real-time analytics, content management systems, IoT, mobile apps, analytical sites | eCommerce sites, high-security sites, structured data with clear schema, social media sites, etc. |
| Data Representation | Represents data as JSON documents | Represents data in tables and rows |
| Supported Languages | C, C++ | C, C++, JavaScript |
| Supports | Inbuilt replication, sharding, and auto elections | Master slave and master replication |
| Schema Definition | No need to define the schema, just need to drop documents | Needs to define tables, and columns prior to storage |
| Query Language | JavaScript as a query language | SQL as a query language |
| JOIN Support | Does not support JOIN operations | Supports JOIN operations |
| Managing Data | Can easily manage large chunks of data | Slow with respect to handling large chunks of data |
| Ideal For | Those projects where there is structured/unstructured data for growth | Those projects where there is structured data and must for a traditional RDBMS |
| Risk of Cyber Attacks | There is no schema definition needed hence the minimal risk of attack owing to design | There is a higher risk of injection attack in this case |
| Foreign Key | Does not support the use of foreign keys | Supports usage of foreign keys |
| Scalability | Can be scaled horizontally and vertically | Can be scaled vertically |
| Terminologies Used | Table
Row Columns Joins |
Collection
Document Field Embedded Document |
| Community Support | Approx. 177k repositories and 923k commits on GitHub for MongoDB | Approx. 222k repositories and 7 million commits on GitHub for MySQL |
| Application Security | It uses a role-based access control (RBAC) | It uses a privilege-based security model (PBSM) |
| User Friendliness | Easy for developers to use because of its easy-to-use interface | Little confusing for developers owing to tables, schemas, normalization, etc. |
| Architecture | Goes by the Nexus architecture with more flexibility | Goes by the client-server architecture with more storage |
| Distributed Architecture | Yes | No |
| Transaction Model | It follows the BASE model with more accessibility | It follows the ACID model with increased consistency |
| Developer Productivity | MongoDB fastens the development cycle and hence is a developer’s delight | Development in MySQL is a little slow as it deals with stringent table structures |
| Integration Support | Integrates well with many storage engines and uses JSON language and MongoDB query language | Makes use of SQL for database management and supports programming languages but is less flexible than MongoDB |
| Query Language | Uses MongoDB Query Language (MQL) which is quite expressive | Uses Structured Query Language (SQL) like any other RDBMS |
| Associated Indexes | If the index is not found, the database engine looks for documents and collection | If the index is not found, the database engine looks for the entire table for the rows |
| Schema Design Flexibility | Supports dynamic schema, design can be changed | Once defined, the schema design cannot be changed |
| Atomic Transactions | Supports multi-document transactions | Supports atomic transactions |
When To Use What: MongoDB or MySQL?
While comparing MongoDB or MySQL, you can choose MongoDB when
- There is a need for high data access and volume with faster data recovery
- Involvement of Big Data across locations is there
- There is a need to lessen schema migration costs in an unstable schema
- Association of native and cloud-based architecture is there
While comparing MySQL Vs Mongo, you can choose MySQL when
- There is a need for a DBMS for a small project with low costs involved
- The data structure and schema are fixed
- The transaction rate is higher
- Data security, reliability, and consistency stand on priority
Good Read: Cassandra vs MongoDB: Comparing Two Popular NoSQL Databases
MongoDB vs MySQL: The Wrap Up
As we enjoy the comparison – of MongoDB vs MySQL, we see different features and architecture that apply to different scenarios. There is no concept of “one size that fits all” here. Based on parameters like size, domain, technology, skilled expertise, budget, deadlines, etc., one can be chosen between the two.
As we leverage the robust and wide-ranging Big Data Analytics Services, managing the storage, transaction, analysis, and maintenance of unstructured heaps of data in a prearranged and skillful manner for real-time visualization and forethought, it is interesting to compare MongoDB vs MySQL.
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