Supervisor(s): Josef Hofer

Abstract: 

Data recording is a fundamental capability of the RTC Toolkit, enabling offline analysis, troubleshooting, performance investigations, and long-term data preservation. Today, recorded data is primarily stored using FITS and JSON Lines formats, both of which have served their purpose but may not fully exploit the capabilities of modern data storage and analytics ecosystems.

This project will evaluate contemporary data recording technologies and file formats, including solutions such as ASDF, Parquet, SQLite, and emerging alternatives, with the goal of identifying opportunities to improve performance, usability, scalability, interoperability, and long-term maintainability.

The outcome will be a comprehensive technical assessment and recommendation document that compares candidate technologies against RTC-specific requirements. The findings will provide a clear basis for future decisions regarding data recording strategies across the RTC software landscape and help reduce long-term technical debt by aligning the platform with modern industry practices.