Parquet Format

Parquet Format is an open-source, columnar storage file format designed for efficient data compression and high-performance analytical queries. It structures datasets by columns rather than rows, minimizing the amount of data read from storage.

How it Works

Parquet optimizes data layout for analytical engines that typically query specific columns.

• Columnar Layout: Groups records into row groups and stores values for each column contiguously on disk, allowing query engines to skip unreferenced columns.
• Efficient Compression: Applies specialized compression algorithms (such as Snappy or Gzip) and encoding schemes (such as dictionary encoding or run-length encoding) tailored to column data types.
• Embedded Metadata: Includes file footers containing schema definitions and basic statistics (such as min and max values) for each column block, enabling query engines to skip irrelevant row groups.

Lakehouse & Agentic Relevance

In a data lakehouse, Parquet is the standard file format used by transactional engines like Apache Iceberg. For analytical agents running SQL, querying Parquet files directly reduces input-output (I/O) bottlenecks. Dremio leverages Parquet’s column statistics and layout, reading only the necessary data blocks to accelerate queries. This performance boost enables real-time responses for conversational business intelligence applications and agents.