Nevados: Optimizing Solar Data Management with Time-Series Database

With the advent of the IIoT in the rapidly growing renewable energy sector, devices are generating more data than ever before. Some of the larger renewable operators generate over 1PB of time-stamped data annually. This ever-increasing data volume presents significant challenges for enterprises trying to manage and leverage the data to gain timely insights, such as real-time monitoring and predictive maintenance. 

Before switching to TDengine, Nevados Engineering, a leader in making single-axis solar tracker for non-flat terrain, was using a key-value NoSQL database. While this solution was easy to get started with, its limitations became evident as Nevados completed more projects and collected more data. The NoSQL database failed to perform acceptably as the business scaled, and it was difficult to query, which meant engineers had trouble accessing the data they needed when they needed it.

Join the webinar to learn the data challenges facing renewable industry and how Nevados utilizes a high-performance time-series database to optimize their solar tracker data management and easily scale their data pipeline as they expand their solar operations and build more sites across the country.