All About Parquet Part 02 - Parquet's Columnar Storage Model

Columnar storage is a data storage model used by Apache Parquet, where data for each column is stored separately, offering significant benefits for big data analytics. This model is efficient for workloads involving analytical queries, large datasets, and data warehousing. Columnar storage improves query performance by allowing the system to scan only the relevant columns, reduces storage costs through better compression, and facilitates efficient aggregation and batch processing. Parquet organizes data into row groups and pages, which are optimized for compression and read performance. While columnar storage is ideal for read-heavy, analytical workloads, it may not be suitable for transactional systems requiring frequent updates. Parquet's columnar model makes it a powerful tool for big data analytics, especially in environments where queries target specific columns. The next blog post will explore the file structure of Parquet, including pages, row groups, and columns.