Hippo Innovations scales its AI-powered e-commerce ecosystem with MongoDB

INTRODUCTION

Hippo Innovations is an Indian technology company building AI-powered, scalable ecommerce ecosystems for businesses across the globe. In 2015, the company launched StoreHippo, a fully managed e-commerce platform that allows business-to-consumer and business-to-business enterprises to build, scale, manage, and market their online stores and multi-seller marketplaces, without having to worry about unnecessary IT burden.

StoreHippo has become the leading e-commerce SaaS platform in India, with thousands of global customers across more than 40 different industry sectors. The platform serves over 1.5 billion secure API calls per month, and has heavily invested in building its own proprietary AI capabilities by building an AI-powered enterprise e-commerce ecosystem.

MongoDB is at the core of StoreHippo’s success story—from building StoreHippo on MongoDB in 2015, to now driving AI innovations at scale, Hippo Innovations relies on MongoDB’s intelligent data platform to deliver what they need to run AI in production, including a real-time database, full text and vector search, memory, embeddings, and reranker models.

THE CHALLENGE

Moving beyond database self-management and bolt-on components

Because Hippo Innovations needed to provide fast and engaging mobile-first experiences, as well as customization functionality  and development velocity for its e-commerce merchants, StoreHippo was originally built on MongoDB Community Edition.

“We used traditional relational databases, such as MySQL, in the past. The rigid schema of those databases inhibits how we can customize the product catalog for each customer,” said Rajiv Kumar Aggarwal, CEO and Founder, Hippo Innovations. “When you come to scale those databases, you typically have to re-engineer and denormalize your schema. With MongoDB, you have none of those limitations. As a result we can adapt and scale 3x faster.”

As StoreHippo further scaled, it needed to reduce operational overhead and improve performance optimization. It was also crucial to build and scale on a platform that would enable Hippo Innovations to explore deeper personalization, search, and AI-driven capabilities.

Fast and relevant search is critical to help merchants’ customers quickly discover and buy products online. The StoreHippo platform offered customers a choice of using the Algolia or Azure Cognitive search engines, but this made the technology stack complex and costly.

Having to bolt-on third-party search engines on top of MongoDB Atlas meant that developers had to remap search indexes, adding friction to onboarding new e-commerce sites and product offerings. What’s more, working with multiple query languages and drivers to query the database and search indexes slowed down the pace of application development, impacting query latency.

Hippo Innovations also knew that it was critical to prepare for an AI-driven future. That meant having access to native vector search, and embedding and reranking capabilities directly within its database platform, to ensure fast retrieval and accuracy.

OUR SOLUTION

Migrating to MongoDB Atlas for scale and an AI-powered future

In 2021, after evaluating databases like Azure Cosmos DB, StoreHippo migrated to MongoDB Atlas. MongoDB was selected because it offered 8x larger document sizes, providing much more flexibility in data modeling and storage. Furthermore, Azure Cosmos DB lacked many of the query and aggregation pipeline features StoreHippo’s developers rely on for its e-commerce services, and it would have meant the company would be locked-in to that platform.

MongoDB’s flexible document model and ease of use allows StoreHippo’s developers to handle the massive variability in product catalog and content attributes, along with associated metadata, media assets, and user reviews. Built on a distributed architecture, MongoDB also provides the engineering teams with cloud-native resilience and scale-out to handle peak loads, especially over busy holiday seasons. Furthermore, MongoDB’s multi-cloud flexibility enabled StoreHippo to do a full migration from Microsoft Azure to Google Cloud.

“Our decision was driven by the operational efficiencies MongoDB Atlas unlocked. We can take advantage of the latest releases much faster, and use new MongoDB features to build richer services for our customers,” said Aggarwal. “It is now much easier for us to use advanced data placement policies like multi-region replication to push data closer to our customers in Europe and Australia, providing higher performance and an even better customer experience.”

Today, MongoDB powers StoreHippo’s entire data persistence layer—from the product catalog to orders, inventory and customer management, and payment processing. For security and performance isolation, each merchant is provisioned with their own single-tenant MongoDB database and search engine.

“With a few clicks in the Atlas UI, we can move customer data on-demand, with no downtime,” added Kriti Aggarwal, CMO and Co-Founder, Hippo Innovations. “At the same time, MongoDB's cloud-agnostic architecture is a key advantage for us. The multi-cloud and multi-region capabilities enable us to meet the regulatory, compliance, and data residency requirements of large enterprises across different geographies, while providing the flexibility to deploy workloads where our customers need them.”

StoreHippo is taking full advantage of the MongoDB Atlas platform—the effectiveness of promotional campaigns can be easily exposed to merchants in rich visualizations powered by MongoDB Atlas Charts, while the MongoDB Data API allows StoreHippo’s developers to query the database directly from the client browser over HTTPS, enabling faster delivery of new frontend features.

With personalization, search and AI at the forefront of today’s e-commerce revolution, MongoDB Atlas has also become a key differentiator for Hippo Innovations. StoreHippo is able to take advantage of many built-in capabilities, including MongoDB Search, MongoDB Vector Search, and Voyage AI by MongoDB. Particularly, Hippo Innovations wanted to avoid having to write additional code to make API calls, or manage embedding generation themselves.