In data lifecycle management, hot data and cold data differ significantly in access frequency, mutation rate, and storage requirements. By leveraging GBase 8a's compression algorithms and levels, you can implement a tiered compression strategy that balances storage efficiency and performance.

Compression Algorithms and Levels

GBase 8a offers three main compression algorithms:

HighZ : Storage-first, pursues the highest compression ratio.

RapidZ : Balances load and query performance.

STDZ : Improves compression ratio while maintaining performance.

Compression levels ( 0–9 ) directly affect compression ratio and speed:

Level Characteristic

0 Default, self‑adaptive, balanced

1 Lowest ratio, fastest load

9 Highest ratio, best complex query performance, slowest load

Function mapping: Compress(1,3) equals COMPRESS('HighZ',0) , and Compress(5,5) equals COMPRESS('RapidZ',0) .

Compression Scope

Three granularities are supported:

Global : Applies to all storage nodes in a VC, for strict storage budget…