Apache ORC
Apache ORC (Optimized Row Columnar) is a columnar storage file format designed for efficient data storage and processing in big data ecosystems, particularly with Hadoop. It provides high compression rates and fast read performance by storing data in columns rather than rows, enabling efficient analytics queries. ORC supports complex data types, ACID transactions, and is optimized for use with tools like Apache Hive, Spark, and Presto.
Developers should learn Apache ORC when working with large-scale data analytics in Hadoop-based environments, as it significantly reduces storage costs and improves query performance for read-heavy workloads. It is ideal for use cases like data warehousing, log analysis, and business intelligence where columnar access patterns dominate, such as aggregating specific columns across millions of rows. ORC's integration with popular big data tools makes it a standard choice for optimizing data pipelines in cloud or on-premise Hadoop clusters.