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How MongoDB Emerged As A Leading General-Purpose Data Platform In 12 Years

How MongoDB Emerged As A Leading General-Purpose Data Platform In 12 Years

  • "We offer free online courses in a variety of areas to developers via MongoDB University."
MongoDB

MongoDB is a modern general-purpose database platform founded in 2007 by Dwight Merriman, Eliot Horowitz and Kevin Ryan. Earlier, Google had acquired the trio’s first venture, DoubleClick–an internet advertising company. The company used to serve 400,000 ads per second, a nightmare in terms of scale and agility. This struggle proved to be the inspiration behind setting up MongoDB.

Headquartered in New York, MongoDB has offices in North America, Europe and Asia-Pacific. The company has around 27,000 customers across 100 countries. Analytics India Magazine caught up with Suvig Sharma, senior director (APAC), MongoDB, to understand how the database management platform gained a foothold in the industry.

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AIM: How does MongoDB help businesses and developers build modern data applications?

Suvig Sharma: MongoDB has continuously evolved in the last 12 years, rising through ranks to emerge as the leading general-purpose data platform for modern applications. Right from operational real-time analytics to full-text search to transactional workloads and data lakes, we can handle all those workloads and we do that in a truly distributed fashion. We also offer a database as a service platform across the three major public cloud providers with true multi-cloud capabilities. We’ve always had the developers’ interests at heart. So everything we did was to make their lives easier and to allow them to focus completely on application development and innovation.

We took developers’ feedback and launched MongoDB Atlas five years ago to run MongoDB on a public cloud. Today, Atlas’ annual revenue run rate stands at $400 million. We have enabled developers to use all our features through a single API and started expanding use cases as well.

For the last four years, MongoDB has been the most wanted database for developers to work with by the Stack Overflow survey. We offer free online courses in a variety of areas to developers via MongoDB University. We have 1.5 million people registered with this university, of which 60,000 are from India.

AIM: Tell us about MongoDB’s AI and machine learning applications.

Suvig Sharma: We’ve got customers that use AI with MongoDB for several purposes. One of our customers makes use of the platform to detect fake news; many call centres use AI to analyse audio and text streams to improve customer service; other businesses use it to streamline their day-to-day operations.

We use a flexible document model that ingests a lot of data. AI and machine learning frameworks help in managing this large amount of data.

AIM: What’s MongoDB 5.0 all about?

Suvig Sharma: MongoDB 5.0 makes it easier to support a broader range of workloads, introduces new ways of future-proofing applications, and further enhances privacy and security. 

For a faster and cheaper way to build and run IoT and financial analytics, we have introduced native time-series collections, clustered indexing, and window functions. You can get insights from the time series data, enrich your enterprise data, and drive even better and real-time decisions.

From MongoDB 5.0, we will make versioned API generally available for developers to future-proof their applications; the application code will continue to run unchanged for years without interruption, even as the database is upgraded and improved.

For seamless data redistribution, we have introduced live resharding. With this, users can change the shard key for collections on-demand with the growing workload. This feature prevents database downtime and complex migration.

With MongoDB 5.0, users can now add client-side field-level encryption to multicloud clusters. It is backed by always-on auditing and certificate rotation and helps users maintain a strict security posture with no interruption to applications, and with the freedom to run applications anywhere.

AIM: Tell us about MongoDB’s recent collaborations.

Suvig Sharma: In late 2019, MongoDB acquired Realm, an open-source database for mobile applications. We’re continuing to build on it because it’s a very exciting space to be able to connect right from the edge to the back end server. Some of our major clients using MongoDB Realms include 7-Eleven stores where managers use it to check on the inventory and make real-time observations. Realm helps pilots of a major Asian airline with their data concerns when they move to a region of non-connectivity. They can collaborate with pilots for tasks such as route optimization.

We acquired MLab in 2018. It was founded in 2011 as a cloud infrastructure company that provides database-as-a-service. The deal proved very beneficial in scaling MongoDB Atlas.

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AIM: How does MongoDB manage growing data?

Suvig Sharma: We have designed and built for a scale-out distributed architecture. As the database grows, we use shard key which defines how the user places the data and how to horizontally scale out to as many nodes as required.

We have also introduced online archiving and data lakes. It is very important for IoT applications which typically gather a humongous amount of data. Further, users can also run federated queries to fetch ‘hot’ data from the cloud in an easy manner, without having to move in and out of the cloud object store.

Suvig Sharma: The success of an organisation can not be decompiled from the software and the application they build. The customer is really concerned about building the applications faster and quicker.

So, that really is driving this whole trend where you’re trying to look at ways in which you can simplify your architecture in which you can build faster. For being able to do that, you don’t want to be stuck with a legacy platform at the back end. With a legacy platform, even an update takes up to six months to be effective. We are building modern database management systems to bring down this time to just a few days. Organisations too are looking for a platform that can support that kind of speed and innovation, but with every security measure in place. 

AIM: What are MongoDB’s future plans?

Suvig Sharma: AI, machine learning, low and no code–these are some of the areas we are focusing on. Further, in terms of reach, we are targeting the Unicorns and Soonicorns, along with larger enterprises to adopt MongoDB’s platform.

Using MongoDB not just for customer-facing kinds of apps, but even things in the policy approval process. Such use cases require flexibility, speed, and security. We have been approached by a few leading private banks and even digital lending apps. We are seeing a lot of traction in these fields and would like to explore further.

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