TimescaleDB Hypercore Engine: Achieving Up to 98% Compression for Time-Series Data in PostgreSQL
By
AWS, Kubernetes & Cloud Security Experts – IT Consulting | RoszigIT
Summary
TimescaleDB achieves up to 98% compression for time-series data using its hypercore engine, a hybrid row-columnar storage engine. Unlike PostgreSQL's general-purpose TOAST compression, TimescaleDB employs specialized algorithms including delta encoding, delta-of-delta, Gorilla XOR, and run-length encoding. The article explains how hypercore works and how to configure compression with segmentby/orderby settings to achieve optimal compression ratios for IoT and time-series workloads.
Source
Hacker NewsTimescaleDB Hypercore Engine: Achieving Up to 98% Compression for Time-Series Data in PostgreSQLroszigit.comKey quotes
· 3 pulledTimescaleDB can achieve compression of up to 98% for typical time-series data.
Compressing time-series data requires a fundamentally different approach than the general-purpose algorithms used in OLTP databases.
In TimescaleDB this is handled by the hypercore engine — a hybrid row-columnar engine that uses specialized algorithms: delta encoding, delta-of-delta, Gorilla XOR and run-length encoding.
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