How to Write Better Queries for Time-Series Data Analysis With Custom SQL Functions

SQL is the lingua franca for analytics`, with many NoSQL databases adding SQL interfaces to keep up. Most developers are familiar with SQL, along with data scientists, analysts, and other professionals who work with data. This makes it easier for teams to onboard new members and quickly extract value from the data. Time-series data is ubiquitous, generating millions of data points per second, making complex queries challenging even in SQL. TimescaleDB hyperfunctions simplify time-series analysis by providing purpose-built functions for common queries, such as time-based analysis, time-weighted averages, percentile approximation, frequency analysis, and more. These hyperfunctions are designed to improve productivity, readability, and maintainability of SQL code, and come pre-loaded on every hosted and managed database service in Timescale Cloud.

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