Mongodb - The 2018 Database

MongoDB is changing the Business of Big Data

Modern data is vast, unstructured, and at times unwieldy. It’s big and complicated, and we have big expectations for what it can do—and trying to store, process, and analyze all of it has led to the development of NoSQL databases. These document-based databases eschew the table-based structure of relational databases and let us group data more logically.

                                       

The leading NoSQL database, MongoDB, has come out ahead in the field for a few reasons. It is an open-source and cross-platform compatible data model. It also has some impressive built-in features that make it an excellent choice for businesses that need fast, flexible access to their data, whether it’s to make real-time, on-the-fly decisions, or to create tailored, data-driven experiences for users. It is also compatible with .NET, Java and more. It’s been used by organizations like Metlife, Sony, eBay, Cisco, HTC, Hackerrank, Twitter, IBM, The Weather Channel, Bosch, Google, Facebook and Expedia, etc.

                                     

When all of the other components of your networked application are designed to be fast and seamless, our data shouldn’t be the bottleneck—and MongoDB is able to meet new data challenges that are difficult to accomplish well. MongoDB enables us to:

1. Store large volumes of data that often have little to no structure. Relational databases store structured data like a phonebook. But for growing, unstructured data—for example, a customer’s preferences, location, past purchases, and Facebook likes—a NoSQL database sets no limits, and allows us to add different types of data as our needs change.
2. Make the most of cloud computing and storage. Cloud-based storage is an excellent cost-saving solution, but requires data to be easily spread across multiple servers to scale up. MongoDB can load a high volume of data and give you lots of flexibility and availability in a cloud-based environment, with built-in sharding solutions that make it easy to partition and spread out data across multiple servers.
3. Develop and release quickly. If we’re developing within two-week Agile sprints, cranking out quick iterations, or needing to make frequent updates to the data structure without a lot of downtime between versions, modifying a relational database will slow you down. With MongoDB’s dynamic schemas, we can try new things, and fast. 
4. Scale database architecture efficiently and inexpensively. With MongoDB, it’s easy to spread data out across commodity hardware on-site or in the cloud without needing additional software.

MongoDB is now becoming an essential part of any Database development in the real world. It is an interesting and indispensable database model to work with.

By:

Navya Mathur

3rd Year