Uses Of MongoDB_ An Imperative Perspective

1. Uses Of MongoDB: An Imperative Perspective NoSQL databases are specially designed to cater to handling big chunks of data. They are designed to scale well horizontally across multiple servers. MongoDB’s built-in support for sharding enables developers to scale clusters just by adding machines. This feat is extremely easy to accomplish in a cloud environment, which ensures minimal latency. This approach is not only easy but also more cost-effective than businesses used to have. Earlier, enterprises had to provide their data centers with enough server storage and CPU resources for the highest use cycles and had to leave their systems underutilized when loads decreased. However, with MongoDB database, developers need not worry. Caching and High Availability MongoDB’s capability to effortlessly create replicas makes it natural for applications that demand high availability. If a primary server goes down, MongoDB database can swap in a secondary server to take over as the primary server. Meanwhile, data can be cached on servers close to users who need it, further minimizing latency for data analysts who want the latest data to create business reports.

2. Rapid Prototyping NoSQL Databases are well-suited for businesses that build new products. Specifications and capabilities often change during the development process, especially at the prototyping stage. Prototyping is referred to as the experimental process where design teams turn ideas into tangible forms from paper to digital medium. When Mongodb developers utilize a relational database with a defined schema, it takes a lot of time in revising data structures and converting data. In a rapid development environment, developers would require to do that over and over again. MongoDB Database, on the other hand, has no rigid schema. It just contains key-value pairs of documents which provide developers with more flexibility. Streaming Feeds Document databases are alternatives to data warehouses for rapidly changing datasets. As the name suggests, a data warehouse utilizes a columnar relational database in which data is structured and well-organized. This ensures a fast repository for analytics, however, the repository is extremely inefficient when it comes to updating and inflexible when schemas change. MongoDB Database includes a feature named Change Streams. These are real-time streams of all changes that occur in the database. If the application inserts, updates, or deletes any of the data in the collection, MongoDB database triggers a change event and highlights all the data that is modified across all replicas. This makes MongoDB a great backend for applications that manage streaming feeds. Content Management and Cataloging Content-based applications are a special case of streaming feeds. For instance, in a retail shop, new products go and come very often. Consequently, product inventories change as units are sold and price changes too. Hence, developers can create data models based on the retailer’s requirements in the form of JSON to represent the way the company handles inventory and sales with a flexible and dynamic structure that even a novice can modify easily. [ Read More: Uses Of MongoDB: An Imperative Perspective ]