ORC (Optimized Row Columnar) is a self-describing, type-aware columnar file format designed for Hadoop workloads. It is optimized for large-scale data processing and storage, offering significant improvements in performance and storage efficiency compared to traditional row-based formats like CSV or text files. ORC files store data in a columnar format, which allows for efficient retrieval of specific columns without reading the entire row. This is particularly beneficial for analytical queries that only require a subset of the data. The format also supports various compression techniques (e.g., Zlib, Snappy, LZO) to reduce storage space and I/O overhead. Furthermore, ORC files include metadata such as statistics about the data within each column, enabling query optimizers to skip irrelevant data blocks and further improve query performance. ORC is widely used in big data ecosystems like Apache Hive, Apache Spark, and Presto for storing and processing large datasets.