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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

How compression codecs work, why Zstandard became the default, how encodings differ from codecs in Parquet, and which codec to pick for each lakehouse workload.

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The File Format Renaissance: Parquet, Lance, Vortex, Nimble, BtrBlocks, and the New Physics of Columnar Storage

The File Format Renaissance: Parquet, Lance, Vortex, Nimble, BtrBlocks, and the New Physics of Columnar Storage

How Parquet, Lance, Vortex, Nimble, and BtrBlocks differ in encodings and point-lookup speed, and which columnar file format fits which workload in 2026.

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Enforcing Fine-Grained Security at Machine Speed: Dynamic Access Control for High-Frequency AI Agents

Enforcing Fine-Grained Security at Machine Speed: Dynamic Access Control for High-Frequency AI Agents

How to secure high-frequency AI agents with dynamic access control: row, column, and tool policies, short-lived credentials, token exchange, and audit trails.

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Implementing Positional Deletes in Iceberg v3: Streamlining Merge-on-Read for Fast-Inbound Event Lakes

Implementing Positional Deletes in Iceberg v3: Streamlining Merge-on-Read for Fast-Inbound Event Lakes

How positional deletes and deletion vectors support merge-on-read in Iceberg for late, duplicate, and corrected event data, plus compaction and engine checks.

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