You are currently viewing We are just getting started: MongoDB’s Sachin Chawla on building solutions for India

We are just getting started: MongoDB’s Sachin Chawla on building solutions for India

MongoDBbegan its journey in 2007 at the time when cloud computing was taking off and the market for scalable and agile database solutions was opening up. 

An open-source NoSQL database management programme, MongoDB helps in storing and managing data. It allows developers to focus on the data they need without the constraints of traditional relational databases.

Today, the New York-based company holds nearly half of the market share in NoSQL databases category. For context, the NoSQL market has players such as Amazon DynamoDB and Apache Cassandra, and is expected to reach $86.3 billion by 2032, according to Allied Market Research. 

Founded by Dwight Merriman, Eliot Horowitz and Kevin Ryan, MongoDB began its India operations in 2013. 

YourStory spoke with Sachin Chawla, the Vice President for India & South Asia at MongoDB, who oversees the expansion and growth of MongoDB in the APJ region to understand the company’s future plans. 

Chawla has 19 years of experience in sales leadership roles in cloud, global software, SaaS, and IT service sectors, serving at companies such as HCL Technologies, BMC Software, and AWS (Amazon Web Services).

Edited excerpts:

Yourstory (YS): Could you provide an overview of MongoDB’s current position in the Indian market? 

Sachin Chawla (SC): India has one of the world’s largest developer ecosystems with over four million developers, and at least 20% of Forbes 2000 companies have established their development centres in India, making the country a significant hub for MongoDB’s operations. 

Our customers in India include Upstox, Darwinbox, Canara HSBC Life Insurance, Magicpin and TATA AIG General Insurance.

MongoDB has initiated an academic programme aiming to train 500,000 students in India to help foster local talent. 

YS: In what ways does MongoDB’s database management system empower startups in India? 

SC: By prioritising developer productivity, MongoDB empowers Indian startups to streamline and accelerate application development. Being a document-oriented database, MongoDB stores data as documents, providing a natural and developer-friendly approach. 

Documents are self-containned and can be treated as objects, enhancing ease of work for developers. This means that developers can focus on the data they need to store and process, rather than worrying about how to split the data across different rigid tables. 

MongoDB Atlas Data Platform addresses all aspects of application data management. By managing the entire data lifecycle, it eliminates the need for startups to invest in multiple technologies. 

Indian startups using MongoDB include edtech startup PhysicsWallah and neobank Flobiz.

YS: Could you share some initiatives that MongoDB has undertaken to establish itself as a preferred partner for startups in India? 

SC: Globally, MongoDB offers several initiatives for startups through its MongoDB for Startups programme. This initiative provides free credits for MongoDB products, including Atlas Database, Atlas Search, Atlas App Services to help startups deal with their data infrastructure. 

We also offer one-on-one sessions with experts to help founders grow their businesses and solve problems. Startups can engage with MongoDB’s community of startups and developers through events and co-marketing initiatives. 

The programme is intended for startups at Series A or earlier that are building a product or service. MongoDB also works closely with VCs, accelerators, and incubators to refer startups to the programme. 

We also launched the AI Innovators Programme, which includes the AI Startups track for early-stage ventures and the AI Amplify track for more established organisations. The programme provides eligible organisations with up to $25,000 in MongoDB Atlas credits to build AI-powered applications.  

Community events and MUG (MongoDB User Group) sessions aim to bring the developer community together, with existing and new users. We also offer MongoDB University, where anyone can sign up for free to learn MongoDB skills. 

YS: How significant is India for MongoDB?

SC: An IDC report estimates that the database market will be $137 billion by 2026 which is a massive opportunity for us globally. 

India has a vibrant ecosystem of startups, enterprises, and SMEs, and we are building solutions for India and the world. India remains a strategic market for MongoDB, we continue to invest in it and we are just getting started.

The country has more than four million developers across a vibrant ecosystem of startups, enterprises, and SMEs, and we are building solutions for India and the world. India remains a strategic market for MongoDB, we continue to invest in it and we are just getting started!

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YS: How many startup clients is MongoDB currently managing in India? 

SC: MongoDB has thousands of customers in India, many of which are startups and Independent Software Vendors (ISVs), spanning early to late-stage development. 

One notable success story is Darwinbox, a tech startup that has experienced growth since it began in 2015. 

The HR Software-as-a-Service (SaaS) platform serves more than 2.2 million daily users. The company started using MongoDB Atlas in December 2017 and MongoDB is its primary database, which helped the company lower costs by 40%.

Another customer example is trading platform Upstox. The platform uses MongoDB Atlas to power the operations of its customers with things like registration, user profile, trading, payments, and ledger. 

YS: How does MongoDB leverage AI, particularly in features like MongoDB Atlas Vector Search?

SC: MongoDB is integrating AI into its products and services, to help developers reduce repetitive tasks and enhance productivity. 

One of the features named MongoDB Atlas Vector Search makes it easy for developers to add generative AI and semantic search features to real-time applications, enabling personalised user experiences. 

Semantic search features refer to capabilities within a search system that go beyond keyword matching to understand the context of words or phrases. 

Edited by Affirunisa Kankudti

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