Case Study: Manage achieves 10x faster data freshness with SingleStore

How Manage Accelerated Data Freshness by 10x

Manage is a technology company specializing in programmatic mobile marketing and advertising, helping drive app adoption for brands like Uber, Wish, and Amazon. As its data volume grew to more than a terabyte per day and over 30 billion bid requests, Manage’s existing MySQL and then Hadoop/Hive/Kafka-based pipeline struggled with scaling and slow Hive performance, creating hours of delay in data freshness. Manage turned to SingleStore to find a faster platform for real-time reporting and ad hoc analytics.

Using SingleStore Streamliner to stream log data from Apache Kafka into the SingleStore columnstore, Manage built a scalable, real-time data pipeline that de-duplicates and aggregates data into summary tables for reporting dashboards and APIs. With SingleStore, Manage reduced data freshness delay from two hours to just 10 to 15 minutes, while also enabling its analytics team to run ad hoc queries on log-level data within seconds.

Manage

Kai Sung

Co-Founder & Chief Technology Officer