The High-Performance Choice: Parquet

For advanced AI projects involving millions of games, simplicity must yield to performance. Parquet is a binary, columnar storage format. Unlike CSV and JSON, which are "row-based" (they read one complete record at a time), Parquet is optimized to read data by column.

Parquet teaches a key Computer Science concept: efficiency through structure. If an AI only needs to analyze the pawn structure (one column) across a million positions, Parquet lets the engine read only that specific column's data, skipping all the irrelevant data (like castling rights or halfmove clocks). This results in dramatically smaller file sizes and much faster queries, which is essential when dealing with Big Data and resource-intensive machine learning training.