To address the challenges of scaling complex data queries efficiently, Apache Druid has incorporated two community extensions, Netflix's Spectator Histogram and Kong's DDSketch, to enhance statistical analysis. Spectator Histogram offers storage optimization for percentile calculations on positive integer values, making it particularly effective for common metrics in cloud services and web applications by reducing data size without compromising accuracy. This extension is especially beneficial for scenarios requiring efficient data representation, although it is limited to positive integers. On the other hand, DDSketch focuses on improving accuracy at the extremes of statistical distributions, specifically for high-percentile measurements like P90 and P10, which are crucial for latency measurement. DDSketch prioritizes true value error over rank error, providing a more stable and memory-efficient solution for high-cardinality data. Both extensions offer significant improvements in storage and computational efficiency, making them valuable tools for real-time data analysis and interactive queries within constrained memory environments.