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Dev.to
7/13/2026
A Deep Dive Into File Compression: How Data Gets Smaller, Why Codecs Differ, and What to Actually Use in the Lakehouse

A Deep Dive Into File Compression: How Data Gets Smaller, Why Codecs Differ, and What to Actually Use in the Lakehouse

Short summary

A comprehensive guide to lossless compression theory and practice for data lakehouses. Covers entropy and the pigeonhole principle as foundations, then walks through every major codec (gzip, Snappy, LZ4, Zstandard, Brotli) with honest trade-offs. Concludes with a practical playbook for configuring compression in Parquet and object storage environments.

  • •Explains compression theory from information theory fundamentals through codec-specific trade-offs
  • •Compares gzip, bzip2, LZMA, Snappy, LZ4, Zstandard, and Brotli with design centers and use cases
  • •Provides practical lakehouse compression guidance for Parquet, columnar encodings, and object storage economics

Generated with AI, which can make mistakes.

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