Column-oriented databases store data in columns rather than rows, which allows for efficient data retrieval and analysis. This structure is particularly beneficial for analytical queries that require accessing large volumes of data but only a few columns, making it faster and more efficient than traditional row-oriented databases. These databases are commonly used in big data applications and business intelligence, where quick access to specific data points is crucial. Examples of column-oriented databases include Apache Cassandra and Google Bigtable, which are designed to handle large datasets and provide high performance for read-heavy workloads.