Case Study: Paytm achieves sub-second, PB-scale analytics with Imply and Druid

Paytm Built a PB-scale Analytics Application using Druid with Imply

Paytm, India's largest mobile payments platform, faced a challenge in managing its enormous data volume of 5 billion daily events. Their legacy analytics solution was slow and complex, hindering the Growth team's ability to gain insights. While an initial move to open-source Apache Druid improved query speeds, scaling the self-managed cluster consumed excessive engineering resources for maintenance and optimization, limiting development.

By adopting Imply's enterprise distribution of Druid, Paytm found a solution. Imply provided a reliably fast platform that required zero DevOps effort to manage. The results were significant: Imply's expertise helped cut AWS infrastructure costs in half and freed up 12 engineering hours per week. Furthermore, query performance improved dramatically, with data sets queried 10 to 35 times faster, enabling real-time analytics across petabytes of data.

Paytm

Ravi Maurya

Technical Lead