Why performance matters in time-series data

The exponential growth of data, particularly time-series data, necessitates new methods of storage and processing that prioritize efficiency and sustainability, given that most of today's data has been generated in the last decade. Despite the projected surge to 175 zettabytes of global data by 2025, a significant portion of enterprise data remains unused for analytics. Time-series data, which captures every fluctuation in variables like weather or machine performance, requires high-performance systems due to its explosive nature and the sheer volume of data points it generates. With the diminishing returns of hardware advancements, attention is shifting toward optimizing software to manage this data more effectively and cost-efficiently. QuestDB exemplifies this approach by developing high-performance solutions that reduce reliance on hardware improvements and cloud costs, thus enabling better decision-making with fewer resources.