Case Study: Meesho achieves scalable, real-time e-commerce growth with Databricks

E-commerce democratized for millions of users in India

Meesho, India’s e-commerce marketplace for millions of users and small businesses, was struggling to keep up with rapidly growing data volumes as it expanded toward a direct-to-consumer model. Its existing platform had limited scalability, high operational complexity, and data latency of three to four hours, making it difficult to support real-time analytics, machine learning, and personalized shopping experiences at scale. Meesho turned to Databricks and the Databricks Data Intelligence Platform to address these challenges.

With Databricks, Meesho migrated to a lakehouse architecture that improved data ingestion, enabled AI use cases such as shopper behavior analysis, inventory recommendations, and fraud detection, and reduced total cost of ownership. The platform helped Meesho scale more easily and cost-effectively to meet multi-petabyte data demands, allowing the company to focus on delivering better experiences for customers and suppliers while reducing operational complexity and runaway costs.

Meesho

Katreddi Kiran Kumar

VP Data Platform