Case Study: Vicomi cuts DevOps time from weeks to minutes and boosts analytics performance with Upsolver

How VICOMI Cut DevOps Time from Weeks to Minutes By Switching from Spark to Upsolver

Vicomi, a marketing-technology and content-analytics provider that tracks emotional reactions to web content, was processing tens of millions of events daily (several billion monthly) into JSON files on S3 using a Spark/Databricks stack. The system was slow to change and hard to maintain—every dashboard change required Python coding and weeks of DevOps—so Vicomi turned to Upsolver’s Data Lake Platform for S3 data management and preparation to simplify analytics on streaming data.

Upsolver replaced the Spark-based pipeline (Kinesis → Upsolver → S3 → Athena/Elasticsearch), enabling Vicomi to build new tables and aggregations via a drag-and-drop UI with no code. The move cut DevOps time from weeks to minutes, let a single developer maintain the data lake, improved Athena performance and dashboard update times, and delivered low-latency access to analytics for customers—demonstrating clear operational and performance gains from Upsolver.

Vicomi

Sagi Waitzman

Chief Technology Officer