What open-source file format provides faster metadata operations for large tabular data sets?

The optimal choice for faster metadata operations when dealing with large tabular data sets is the Delta Lake format. Delta Lake builds on top of Apache Parquet and adds a layer of ACID transactions and schema enforcement, allowing for efficient management of large datasets. It maintains a transaction log that provides strong consistency and enables fast queries while ensuring that the metadata is readily accessible and can be updated quickly.

This feature is particularly important in big data environments where the performance of metadata operations can significantly impact overall data processing speeds. Delta Lake allows concurrent reads and writes, which further enhances its efficiency in handling large volumes of data compared to formats like JSON or CSV, which do not have such sophisticated metadata management capabilities. Consequently, while Apache Parquet is a powerful file format, Delta Lake's combination of performance enhancements and advanced features makes it superior for managing large-scale datasets effectively.