Statistical and Analytical
Quantile
Efficient quantile and percentile calculations in PostgreSQL
The quantile
extension provides efficient computation of quantiles and percentiles in PostgreSQL. It’s particularly useful for statistical analysis, performance monitoring, and data distribution understanding.
Your Nile database arrives with the quantile
extension already enabled.
Understanding Quantiles
A quantile divides a dataset into equal-sized groups. Common examples include:
- Median (50th percentile)
- Quartiles (25th, 50th, 75th percentiles)
- Percentiles (dividing data into 100 groups)
- Custom quantiles (any division between 0 and 1)
Quick Start
Let’s explore quantile calculations with practical examples.
Creating a Table with Sample Data
Basic Quantile Calculations
Calculate median response time:
Calculate multiple percentiles:
Rolling Percentiles Example
This query will show you the 50th, 90th, 95th, and 99th percentiles of response times for each API endpoint, grouped by hour over the last 24 hours.
Common Use Cases
-
Performance Monitoring
- Response time percentiles
- Resource usage distribution
- SLA compliance monitoring
-
Financial Analysis
- Price distribution analysis
- Risk assessment
- Portfolio performance metrics
-
Quality Control
- Process variation monitoring
- Outlier detection
- Manufacturing tolerances