Case Study: BEET Analytics achieves 1–2 orders of magnitude better performance and higher manufacturing throughput with MongoDB

Beet Analytics - Customer Case Study

BEET Analytics builds Envision, a Process Visibility System that monitors automated assembly lines at the motion-and-event level to prevent downtime and maximize throughput. The company needed to ingest and analyze millions of telemetry records per day (about 1–3M documents per line, ~500M retained over months) and found their SQL Server-based approach could not scale without expensive hardware.

BEET embedded MongoDB in Envision—deploying per-line data collectors and a central replica set and using aggregation/map-reduce for analytics—to handle high-frequency telemetry. The MongoDB-based solution delivered 10–100x better performance than SQL Server, lowered infrastructure costs, enabled faster product development, provided reliable failover, and improved manufacturing throughput through timely predictive alerts.

Beet Analytics

Girish Rao

Director of Core Development