In broad terms, Vector uses columnar storage. While data is stored and retrieved in familiar relational rows, the internal storage is different. Instead of storing all column values for a single row next to each other, all rows for a single column are stored together. This storage format has benefits for data warehouse applications, such as reduced I/O and improved efficiency.

A relational table may have dozens or hundreds of columns. In traditional row-oriented relational storage, the entire row must be read even if a particular query requests only a few columns. With column-oriented storage, a query that needs only a few columns will not read the remaining columns from disk and will not waste memory storing unnecessary values. A side benefit of this columnar storage is that compression (see Data Compression) can be more effective.

While Vector is fundamentally a column store, it is not strictly so. For certain types of tables, Vector stores data from more than one column together in a data block on disk. Within a data block the values for each column are kept together so that data for a column can be processed efficiently in vectors. Vector also provides a storage type that lets you indicate you want to store all columns for a table in a single block.