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 control.…