# Storage Formats | Account number | Last name | First name | Purchase (in dollars) | | -------------- | --------- | ---------- | --------------------- | | 1001 | Green | Rachel | 20.12 | | 1002 | Geller | Ross | 12.25 | | 1003 | Bing | Chandler | 45.25 | ### Row Oriented Storage In a row-oriented DBMS, the data would be stored as 1001,Green,Rachel,20.12;1002,Geller,Ross,12.25;1003,Bing,Chandler,45.25 Best suited for OLTP - Transaction data. ### Columnar Oriented Storage 1001,1002,1003;Green,Geller,Bing;Rachel,Ross,Chandler;20.12,12.25,45.25 Best suited for OLAP - Analytical data. 1. **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. 2. **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. 3. **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.