Company and use case

Palas, a German company established for nearly 40 years, specializes in advanced air quality measurement devices used globally. Their instruments, present in numerous countries and even remote locations like Antarctica, are crucial for various applications, including smart city projects, construction site monitoring, and environmental research. These devices provide real-time data on air quality, helping cities integrate environmental monitoring with traffic data, ensuring construction sites comply with pollution regulations, and aiding in assessing natural disaster impacts.

Performance problems to solve

Palas faced several technical challenges due to the high volume of data generated by their devices. They required a solution that could handle efficient real-time data ingestion, storage, and complex querying capabilities. Additionally, the need for a cost-effective and scalable system was paramount to manage the growing dataset without incurring prohibitive costs for development and maintenance. The ability to provide flexible data access to a diverse clientele, including real-time alerts and historical data analysis, was essential.

Performance gains unlocked

Implementing TimescaleDB brought significant performance improvements for Palas:

• Data Compression: Enabled a 4x reduction in database size, shrinking from 200 GB to 55 GB.

• Query Performance: Maintained average query times of 25 milliseconds for complex data retrieval.

• Insertion Rate: Achieved a high insertion rate of 0.3 milliseconds per data point.

• Resource Efficiency: Operated the database on minimal resources (2 CPUs, 4 GB RAM) while handling high-frequency data ingestion and complex queries.

These improvements allowed Palas to offer efficient, real-time data access and analysis capabilities to their customers, supporting a wide range of environmental monitoring applications with reduced operational costs and enhanced performance.