MongoDB’s Atlas document data storage model helps developers build responsive and highly scalable applications
Modern applications for customers need to be highly responsive, analytics forward, mobile first, have relevant information, provide data privacy, and always improve. Here’s how MongoDB is helping developers build them.
If you’re a startup or enterprise and looking to scale your product or service, the most efficient way to do so would be by leveraging your data to constantly improve and innovate your solutions for customers.
Elaborating why it’s become so important today to do so, Vinay Agarwal, Senior Enterprise Solutions Architect, explained, “The most competitive advantage companies have is how well they build using data.”
Speaking at his masterclass on ‘Building the next big thing’ at TechSparks 2022, Vinay said that 70 percent of enterprises fail in digital transformation goals because true data innovation cannot be bought and they need to enable sustainable innovation.
The data dilemma
“Working with data has always been the hardest challenge. While companies have built a lot of different applications, new technologies have come in, and you have changed a lot, the underlying data infrastructure hasn’t changed much — it’s like layers that have been built over it. This makes the whole architecture complex and difficult to make changes that you want to bring to the market quickly,” Vinay shared.
This layered approach, Vinay said, instead of rethinking their data strategy, leads to issues such as a fragmented developer experience, a significant amount of data integration required, and data duplication, along with each technology layer coming with its own operational and security models. These issues — that MongoDB calls Data and Innovation Recurring (DIRT) Tax — make it tough for developers to implement updates and changes, sometimes taking up to weeks.
MongoDB’s solution
Vinay then illustrated how the document model for data storage that MongoDB’s Atlas developer platform follows gives customers the ability to index, access, and process their data through a single interface, without worrying about any hiccups while scaling and making changes to the actual platform itself.
“While you’re dealing with different models, you’ll still only need to work with a single unified interface through which you can interact with a number of data models. This means developers don’t have to learn different technologies or ways of communicating with the system,” Vinay said.
The platform also allows users to build a reliable search interface, embed analytics and insights dashboards for data visualisation, build app APIs and service functions, sync data across devices and users, and more.
Because of its multi-cloud approach, MongoDB is available on all three public clouds. This means customer platforms could potentially have a few processing nodes on AWS, a couple of others on Google Cloud, and another in Azure, all within the same cluster. It also provides security for data at rest, data in transit, authentication, authorisation, and encryption to make sure you have a variety of compliances and regulatory requirements.
