Parquet File Format: The Complete Guide

The Parquet file format is a structured, columnar data storage solution that offers significant advantages in terms of storage efficiency and query performance, especially for data-intensive operations like machine learning and AI. Unlike row-based formats such as CSV, Parquet's columnar structure allows for efficient data compression and encoding, resulting in reduced file sizes and faster query speeds. This makes it particularly well-suited for use with serverless technologies like Amazon Athena, BigQuery, and Azure Data Lakes. The format supports schema evolution, enabling the addition of new data columns without disrupting existing datasets. While Parquet files are optimized for machine processing and may require additional tools for compatibility, they offer substantial benefits in terms of reduced storage and computation costs, as well as improved analytics capabilities. Parquet's binary format and embedded metadata further enhance its efficiency, making it a compelling choice for modern data storage needs, especially when paired with robust observability solutions like Coralogix.