Deep Dive: How Compression Codecs Impact Data Storage and Query Costs

File compression reduces storage and compute costs by removing redundancy, with codecs like gzip, Snappy, and Zstandard making different trade-offs between speed and ratio. The pigeonhole principle ensures no universal compressor exists, so matching codec to data type is critical. In lakehouse architectures, compression settings directly affect Parquet file size, query latency, and cloud storage bills.