A bitmap index is a data structure used in data warehousing to efficiently process low-cardinality data with repeated values. It requires less memory but may require multiple CPU processes to decompress and editing can be time-consuming.
A bitmap index is a specific type of data structure. In computer science, data structures are methods of organizing and classifying data in order to use it most efficiently. The advantage of using this particular data structure is that certain information can be processed faster and requires less hardware memory. In particular, a bitmap index is commonly used when dealing with data warehousing.
The concept of “data warehousing” refers to a method of organizing huge amounts of data. When data is organized, various trends or patterns can be sifted through and identified so that they can be better understood. This means that the data is sorted in a table and defined by numbers that represent different values in the data. Generally, data indexes of this type are more efficient when the data being defined does not repeatedly include the same values. A bitmap index, on the other hand, is best used when values repeat.
This type of repetition can be described as low-cardinality data, which is when the information displayed may only have a very small number of hits. Thus, the same value would be repeated multiple times. An example of this is when values define masculine and feminine. There are only two different ways to describe gender, so each column in the table would have low cardinality and would be perfect to display with a bitmap index.
Although displaying this type of data in an index allows it to be read more quickly, there is a trade-off. The very condensed structure allows it to be easily read but at the same time the data has to be processed by the CPU multiple times to decompress it into the simplest terms the computer can understand. Also, editing a bitmap index can be time consuming. Since everything is very systematic and specific, one thing that needs to change can cause changes in the whole structure.
Another advantage of bitmap indexes is that they require very little memory. Often, a database index has more components than the data itself and requires additional space to store. When using the bitmap index, this is not the case. Condenses data into smaller, easier-to-read pieces, freeing up space that shouldn’t be used.
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