Standalone Apache Parquet

Introduced in 2013, Apache Parquet is an open-source columnar file format that has become the standard for large-scale data storage and management. Designed to optimize read and write performance on large datasets while reducing storage space requirements, it has replaced flat file formats like CSV in data engineering.

Parquet offers many advantages:

• Significant file compression (up to ten times smaller than CSV),
• High performance: 30 times faster than CSV for reading and writing analytical queries,
• Support for complex data types, including nested structures (lists, dictionaries...),
• Strong integration with major cloud providers and broad compatibility with many open-source tools.

However, Parquet is not ideal for frequent writes or real-time data streaming, where a row-based format like Avro is more suitable.

Formats such as Delta Lake or Apache Iceberg are preferable for ensuring better data governance, handling structural changes in tables, and maintaining data integrity in cases of concurrent writes.

Theodo’s point of view

Parquet remains a solid technology with advantages for analytical workloads due to its performance and storage optimization. Our hold position reflects our recommendation to adopt additional layers like Iceberg to benefit from transactional capabilities and data scalability.

MDN’s point of view

Parquet has become the reference format for analytics. Compressed, columnar, and widely compatible, there are many reasons to use Apache Parquet in 2024. It is preferable to flat formats like CSV or JSON. Essential for saving costs and improving performance. The only drawback is that it is less convenient to open in a graphical interface (unless using DuckDB).