Case Study: Spireon achieves near-real-time IoT analytics — cutting time to insight from 48 hours to 1 minute — with Snowflake

Accelerating Data Analytics for IOT with Snowflake

Spireon is a vehicle-intelligence company in telematics that manages over 4 million connected vehicles and ingests more than 4 billion IoT events per year to serve 20,000+ customers. Their legacy data warehouse and MongoDB reporting infrastructure could not handle massive JSON time-series data, required constant tuning and oversized nodes (driving costs up), and produced a two-day time to insight—preventing near real-time analytics for customers and internal teams.

Spireon migrated to Snowflake’s cloud-built data warehouse, using independent compute clusters, native SQL for semi-structured data, per-second pricing, and instant scaling. The result: eliminated heavy parsing work, supported unlimited concurrency, powered more Looker dashboards, and cut customer time to insight from 48 hours to one minute while delivering an 800% cost savings; Snowflake also enabled secure data sharing and a path to real-time data products and ML-driven analytics.

Spireon

Dave Withers

Director of Analytics