Meta’s OpenZL changes the way data is compressed by maximizing efficiency for structured datasets, outperforming traditional methods like Zstandard. With a universal decompressor and custom compressio

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Meta released OpenZL, an open-source compression framework optimized for structured data like Protocol Buffers, database tables, and ML tensors. Unlike general-purpose compressors that treat data as raw bytes, OpenZL explicitly models data structures to achieve better compression ratios and faster speeds than Zstandard. It features a universal decompressor that executes embedded compression plans, eliminating the need for external metadata and enabling fleet-wide updates from a single binary. Benchmarks show OpenZL achieves 1.64× compression ratio at 340 MB/s compression and 1200 MB/s decompression speeds on structured datasets, outperforming both zstd and xz while maintaining deterministic decompression behavior.

Meta Open Sources OpenZL: A Universal Compression Framework for Structured Data