database

Parquet

Parquet is an open-source columnar storage file format designed for efficient data storage and retrieval in big data processing systems. It optimizes performance by storing data in columns rather than rows, enabling better compression and faster query execution for analytical workloads. It is widely used in data lakes and big data frameworks like Apache Spark, Apache Hive, and Apache Hadoop.

Also known as: Apache Parquet, Parquet format, Parquet files, Parquet columnar, Parquet storage
🧊Why learn Parquet?

Developers should learn and use Parquet when working with large-scale analytical data processing, as it significantly reduces storage costs and improves query performance through columnar compression and predicate pushdown. It is ideal for use cases such as data warehousing, log analysis, and machine learning pipelines where read-heavy operations dominate, and it integrates seamlessly with modern data ecosystems like cloud storage (e.g., AWS S3, Azure Data Lake).

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