Parquet

Apache Parquet is a columnar storage file format designed for efficient analytical processing. Rather than storing data row by row like CSV, Parquet stores each column together - enabling queries that read only the columns they need and dramatically reducing I/O for analytical workloads that touch a subset of fields.

Parquet uses built-in compression and encoding that typically achieves 5-10x smaller file sizes than equivalent CSV data. It also embeds schema metadata in the file itself, so readers know data types without a separate schema definition. These properties make Parquet the preferred format for large datasets used in analytics pipelines.

HappyEndpoint datasets are available in Parquet for customers running analytical workloads where performance and storage efficiency matter. If you are loading data into a tool like Spark, BigQuery, or Athena, Parquet is almost always the right format choice.