3 Ways to Plot Incremental PostgreSQL Materialized Views

The article highlights the advantages of using TimescaleDB for managing sensor equipment and data logging, emphasizing its features like compression, retention, and particularly continuous aggregates for downsampling. Despite these benefits, the author discusses the challenges of effectively plotting continuous aggregates in applications like Grafana, particularly when dealing with different time intervals. To address this issue, the article proposes three solutions: using UNIONs to combine raw and aggregated data based on time intervals, creating inline SQL functions to encapsulate complex queries, and leveraging PL/pgSQL to automate the selection and execution of appropriate aggregates. The author illustrates how these approaches can optimize database performance by reducing the need for constant re-aggregation while maintaining detailed data accessibility, ultimately promoting seamless integration and efficient data management.