MongoDB’s Sachin Chawla on Navigating Data Modernization and Innovation – Brand Wagon News

In a conversation with BrandWagon Online, Sachin Chawla, Vice President, India & South Asia, MongoDB shares his insights on how the company is navigating these changes. As organizations of all sizes—from startups to large enterprises—embrace modernization, MongoDB says it is at the forefront of this transformation. Chawla discusses how MongoDB serves a variety of customers, from digital natives like Zomato and Zepto to large enterprises like Tata Digital and Adani. They also expand on MongoDB’s role in helping businesses build a unified view of the customer with flexible, scalable data solutions. As the demand for innovative and agile data solutions grows, MongoDB continues to drive digital transformation across industries by providing insights on how businesses can remain competitive and efficient in a data-driven world. (Edited excerpts)

Many brands may not have invested in a coherent data infrastructure, especially in sectors like CPG and other consumer-facing industries. How do you see this shift impacting data investment trends in India, especially for companies that traditionally do not deal with extensive first-party data, such as banks or fintechs?

For starters, we serve a diverse set of customers across industries and sizes of companies, from startups to large enterprises and independent software vendors (ISVs). Let me give you a few examples. Among the digital natives, we have big-name customers like Physics Wallah, Zomato, and Zepto. For example, whenever you order food on Zomato and track your delivery person, most of that backend is powered by MongoDB, handling millions of requests to the database. Zepto, a fast-growing fast-paced commerce company, is also building a large part of its infrastructure on MongoDB. They even spoke at our local tech event in Bangalore recently about scaling their platform with MongoDB.

On the enterprise side, we work with companies like Tata Digital. Their loyalty app, Tata Neu, unifies loyalty programs across 40 Tata brands, including hotels, airlines and electronics, allowing customers to earn and spend “NeuCoins” seamlessly. This super app is powered by MongoDB. Similarly, Adani’s airport app, used across seven airports, allows customers to book lounges, shop and manage their travel. We also support major banks as they move from legacy databases like Oracle and SQL to MongoDB, modernizing their operations.

Finally, we have ISVs, companies that build their own software products. A great example is Darwinbox, an HRMS platform built entirely on MongoDB. Our database serves as a horizontal, universal solution, supporting a wide range of use cases across industries and customers.

Data is often associated with marketing. How does MongoDB help marketers better understand the consumer journey and make more informed decisions?

This is becoming essential, especially in the AI-driven world we are heading towards. AI applications rely on massive amounts of data from various sources in various formats. Having a unified view of the customer, often referred to as “Customer 360,” is becoming critical. Many large applications are now building this single view of the customer by aggregating data from multiple sources. Without this, it is impossible to deliver the personalized experiences that consumers expect.

In most enterprises, there are typically three key systems: systems of record (transaction systems), systems of insight (data analysis and insight), and systems of engagement (customer interactions). These systems often work with different applications, leading to data silos. To combat this, companies create an Operational Data Store (ODS) that consolidates all of this data into a single unified source of truth. This is where MongoDB comes in.

MongoDB’s document model is highly flexible, allowing it to store any type of data, whether structured or unstructured—transactional data, PDFs, audio, or video files. Businesses use MongoDB as a unified data store, allowing them to build a comprehensive “Customer 360” view. This helps them better understand and engage in a more personalized and effective way.

MongoDB has seen a significant increase in its operating losses in Q2 FY25. Could you share the annual growth rate for the Indian market and where the squeeze lies between large enterprises and SMEs in terms of business growth?

Globally, we have seen strong growth, with 13% quarter-on-quarter growth and a customer base now in excess of 50,000. In India, we are growing rapidly, with three key areas of focus. First, we continue to focus on the startup and digital solutions segment, such as Zepto and Zomato. Second, large enterprises, especially in the financial sector — banks, fintechs, and other financial services — are the primary target. Third, we are also prioritizing ISVs, as they are a significant contributor to the market, and 80% of software still comes from ISVs.

How does MongoDB Atlas integrate with generative AI technologies and what benefits does this integration offer your customers?

Atlas is our fully managed service available on AWS, GCP, and Microsoft Azure that enables customers to deploy applications in their chosen region or availability zone. It handles administrative tasks such as backups and release upgrades, allowing customers to focus on building applications without worrying about managing infrastructure.

In generative AI, we introduced vector search, a powerful feature that we launched last year. Vector search allows users to represent unstructured data—like video or audio—in a way that AI models can understand by converting it into a multidimensional form. This feature is part of Atlas, making it easier for customers to integrate AI-based solutions. For example, Intellect.ai built its “Purple Fabric” platform for FSI customers who use both Atlas and vector search. Many of our customers use it for a variety of use cases to optimize their AI applications.

What are MongoDB’s key priorities for the next year to compete with relational databases and how will you differentiate yourself? Also, how are you dealing with the challenges in the Indian market, especially price sensitivity and legacy brands?

Organizations need to modernize their legacy systems as technology evolves and consumer demands increase. MongoDB’s strategy is to support this modernization, whether on-premises or in the cloud, based on each organization’s needs. Our priorities include: becoming the standard for large enterprise workloads, especially in the financial sector; excelling in AI and generative AI applications; and improving our developer platform to make it easier to build modern applications. We are committed to adapting to these changes and helping our customers navigate their digital transformation.

How will MongoDB solve the cost challenges for large enterprises and convince them to reduce their operational expenses? And how will you help FMCG companies manage and organize their fragmented retail data?

For large enterprises, the key discussion is often about reducing time to market and increasing innovation, not just costs. Enterprises face intense competition from startups that are rapidly gaining market share. As a result, these companies need to innovate quickly and efficiently to remain relevant. The focus of these conversations is on how MongoDB can accelerate their time to value and help them innovate faster.

For retailers dealing with distributed data, MongoDB offers significant advantages as a unified data store. Our platform can integrate disparate data sources and support a wide range of data types and workloads. This capability allows retailers to consolidate their siloed data into a single, consistent view. For example, we’ve helped various e-commerce and media companies create a comprehensive 360-degree view of the customer, enabling them to manage and leverage their data more effectively.

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