United Manufacturing Hub builds scalable and secure open-source Industrial IoT infrastructure that combines state-of-the-art information and operational tools (IT/OT) and technologies, bringing them into the engineer's hands. Manufacturing data is mainly relational: orders, products, production plans, and shifts are good examples. However, due to the growth of analytics, time-series data gets increasingly important, e.g., for preventive or predictive maintenance.
Previously, United Manufacturing Hub used InfluxDB. They realized that modeling relational data into a time-series database was a bad idea. The continuous queries were failing too often without even throwing error messages. The database could not handle the data buffered somewhere else in the system and thus arrived late. Additionally, Flux as a query language is comparatively new and not as easy to work with as SQL.
It quickly reached the point where they had to implement Python scripts to process data because Flux had reached its limits in use cases that would work seamlessly using SQL. So the team felt like InfluxDB was putting unnecessary obstacles in their way.
Reliability and fault tolerance were the main reasons why United Manufacturing Hub moved to Timescale. The stability of Timescale allows them to focus on developing their microservices instead of fixing breaking API changes.
The reliability of Timescale manifests in the ease of horizontal scaling across multiple servers, which we are very interested in.
Jeremy Theocharis, Co-founder and CTO at United Manufacturing Hub