Company and use case

United Manufacturing Hub (UMH) is an innovative company focused on transforming the manufacturing industry through open-source solutions and advanced data analytics. Their platform provides tools for predictive maintenance, real-time monitoring, and optimization of manufacturing processes. By integrating IoT sensors and leveraging time-series data, UMH helps manufacturers improve efficiency, reduce downtime, and extend the lifespan of machinery, ultimately driving productivity and cost savings.

Performance problems to solve

Before implementing TimescaleDB, UMH faced significant challenges with handling and analyzing vast amounts of time-series data generated by IoT sensors. Their existing database infrastructure struggled with slow query performance, inefficient data retention, and complex maintenance processes. These issues hindered their ability to provide timely insights and predictive analytics, affecting their overall operational efficiency and scalability.

Performance gains unlocked

After adopting TimescaleDB, UMH experienced substantial improvements in data management and system performance. The use of continuous aggregates and automated data retention policies streamlined their data processing workflows. Query speeds increased dramatically, allowing for real-time analytics and faster decision-making. This transformation enabled UMH to scale their operations, reduce maintenance overhead, and deliver more accurate predictive maintenance solutions to their clients.