How enterprises can develop a unified view of handling data using MongoDB’s platform

In a masterclass titled ‘Need to speed: Innovating with MongoDB’, Mohit Bhargava and Nitin Mukheja, Solutions Architects from MongoDB, discuss how their platform can help companies standardise their search and data streamlining capabilities.

Digital transformation is reshaping every industry, with companies doing their best to offer their customers world-class experiences. 

However, the journey of digital transformation is not easy. In a digital world, where there are hardly any barriers to entry and so much data is floating around, the process of digital transformation can be challenging to manage for enterprises.

This is where platforms such as MongoDB come in. MongoDB provides an application data platform that allows one to accelerate and simplify how you build with data for any application.

In a masterclass titled, ‘Need to speed: Innovating with MongoDB’, Mohit Bhargava and Nitin Mukheja, Solutions Architects from MongoDB, discussed how the platform can help companies develop a unified view of handling data. 

Why MongoDB?

Mohit explained that one of the hardest parts of running an application is handling data. He said infrastructure to handle data is still inadequate and short-term redressals cannot fill the gap.

“Sometimes developers use ‘band-aids’ to address the gaps in relational databases, but that is not enough,” he said. 

This is where MongoDB comes in. It’s not just flexible, but also maps out how developers think and code.

“With MongoDB, you can handle graph data, time series data, or any model data you can think of,” he explained.

MongoDB also acquired a platform called Realm, which is integrated into its system and allows the developer to sync services in offline mode. This feature is particularly useful in cases of crypto applications, fleet monitoring, and more.

MongoDB has been deployed across 80 regions, including the likes of Google Cloud, AWS, and Azure.

Key features of MongoDB

One of the key features of MongoDB is that it can handle time series data more efficiently. Time series data refers to a sequence of measurements over a period of time with common properties. 

“Additionally, it tackles some of the common industrial challenges faced by companies with respect to time series data - platform integration, performance at scale, data coupling, and more,” Nitin said.  

MongoDB’s native time series platform solves these challenges by supporting high storage efficiency and low latency queries, unlocking insights faster with new window functions and temporal operators. It provides real-time analysis, visualisation, and online archiving in a secure enterprise-grade platform. 

Nitin also spoke about MongoDB’s search platform Atlas Search, which helps a company search data in the cloud. MongoDB Atlas Search is simple to use, integrated, fully managed, and has rich search capabilities. 

MongoDB is a useful tool to standardise search and data streamlining capabilities, Nitin said. 

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Edited by Teja Lele Desai


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