Compression: Since the data in a column tends to be of the same type (e.g., all integers, all strings), and often similar values, it can be compressed much more effectively than row-based data.
Query Performance: Queries that only access a subset of columns can read just the data they need, reducing disk I/O and significantly speeding up query execution.
Analytic Processing: Columnar storage is well-suited for analytical queries and data warehousing, which often involve complex calculations over large amounts of data. Since these queries often only affect a subset of the columns in a table, columnar storage can lead to significant performance improvements.
