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Hardik Shah works as a Tech Consultant at Simform, a leading custom software development company. He leads large scale mobility programs that cover platforms, solutions, governance, standardization, and best practices. Connect with him to discuss the best practices of software methodologies @hsshah_.

Real World Use Cases of MongoDB and MySQL

Ever since the start of the digital revolution, we have witnessed the utmost requirement of storing data effectively and efficiently. Data is the lifeblood of business solutions and having an accurate database management system (DBMS) is a crucial tool for handling such large volumes of data. 

Each database management system offers specific solutions as per business requirements, and decision-makers are often left wondering which system would be appropriate for their use. MongoDB and MySQL have always been at the forefront of being the most prominent DBMS for various businesses. 

Let’s explore some of the real-world use cases of MongoDB vs. MySQL that make decision-making easy. 

MongoDB and its Use Cases

MongoDB is a document-oriented database classified as a NoSQL database program. Its document data model supports JSON and offers functionality like horizontal scaling, automatic failover, and the built-in ability to assign data to a location. With a flexible data model and unlimited scalability, developers can effortlessly work on indexing and querying as per their requirements. 

Use cases

  • Single View Applications – Large organizations often deal with siloed data that is spread across multiple teams, functions, or classified depending on the type of data. A single view allows the users to access aggregated data from multiple sources in a single page or document. MongoDB’s dynamic scheming and expressive query language make a single view database quick and easy to process information. Examples of this type of application include real-time inventories used in the retail sector, Omni-channels in a single view in government sectors, single view of users across products in high-tech, financial services, etc. 
  • Big Data Management – Big data management has become a critical part for companies handling large volumes of user data that are computationally complex to process by traditional systems. The NoSQL and non-relational structure of MongoDB makes query processing effortless against a wide variety of data, offering velocity and veracity to its users. 
  • Content Management – There has been a growing demand for delivering unique content for capturing user attention and integrating eccentric content features. Unlike static content of the past, a relational database cannot incorporate different forms of content like text, audio, video, tweets, presentations, etc. With MongoDB as a database, a diverse range of content can be stored and served by building new features without impacting its performance or costing extra bucks. Examples include consolidating app backends, publishing government archives online, etc. 
  • Real-Time Analytics – Fast-paced business applications or companies have to change and make decisions instantaneously depending on the market response. A traditional database program won’t have a monitoring system to provide structured and geospatial analytical data. MongoDB provides real-time, lightweight, low-latency analytics that can be integrated with the existing operational database at less cost with the option for unlimited scalability. Examples include analyzing satellite imagery, identifying social frauds based on historical data, recognizing customers in retail sector apps, etc. 

MySQL and its Use Cases

Amongst the popular open-source databases, MySQL is one of the preferred relational database management systems. The Structured Query Language of the BDMS is used to extract, modify, and create data from the relational database and control user access. In addition, the concept of JOIN operations simplifies the relational processing of querying across multiple tables, minimizing data duplication and making it an ideal database management system.

Use cases

  • Online Transactional Processing – While it is natural that MySQL can be deployed for applications in need of a transactional SQL engine, the database can also be used for websites with heavy traffic and mission-critical applications. Its adherence to ACID principles and extensions to ANSI/ISO Standard SQL supports a large volume of databases. 
  • LAMP Stack – For developing a custom web application, LAMP stack has often been the favorite choice of platform. Being an open-source software stack, it is used more than often one would even think about it. The database management of the same applications is often done through MySQL since its simple programming syntax makes it compatible with high-performant apps. 
  • eCommerce Applications – User data, consumer information, and transactional data are an integral part of an eCommerce application, and choosing a secure database is of primary concern. MySQL is popularly used as a transactional engine for applications with a broader customer base and diverse products. It can process a high volume of requests in the shortest amount of time, therefore, improving application performance. 
  • SaaS Applications – With a growing market for SaaS applications, vendors inevitably have to keep up with their application performance. MySQL accelerates performance for SaaS applications with horizontal and vertical scalability. Furthermore, it promises greater security of consumer data and transactions through authentication, encryption, and firewall. 

Conclusion

MongoDB and MySQL can be considered rival database management systems offering similar services, except for some fundamental differences in processing data. 

Depending on the project requirements, selecting the optimal database system is necessary to provide long-term solutions for better data management. While the use cases offer specific details of the DBMS usage, it is always necessary to understand what a database system offers and how it can be implemented for greater business profits.

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