How TimescaleDB compresses time-series data
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TimescaleDB's hypercore engine achieves up to 98% compression for time-series data by converting older row-based chunks into a columnar format, grouping rows into batches of 1000 and applying specialized algorithms like delta-of-delta for timestamps and Gorilla XOR for floats. This contrasts with PostgreSQL's TOAST, which only compresses large variable-length values and yields ~1× ratio for sensor floats, while hypercore reaches 10-100× by exploiting cross-row patterns and numeric structure.
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