What PyArrow Is and How Zero-Copy Data Sharing Actually Works in Python

Apache Arrow is an in-memory columnar data format designed to eliminate the costly data-copying that traditionally occurs when moving data between tools in a Python data stack. Unlike Parquet, which optimizes for compact on-disk storage and requires decoding before use, Arrow stores data in ready-to-compute, uncompressed buffers that CPUs can operate on directly. PyArrow is the Python implementation of this standard, and its zero-copy capability means processes sharing Arrow-formatted data can reference the same memory buffers rather than duplicating them. Arrow represents values such as strings using contiguous fixed buffers — including a validity bitmap, an offsets buffer, and a values buffer — instead of scattered pointer arrays, enabling faster vectorized computation. This architecture is why Arrow has become a common interchange layer across tools like DuckDB, Polars, pandas, and PySpark.