Answer Posted / rahul roshan

Bitmap indexes have traditionally been considered to work well for data such as Boolean values, which have a modest number of distinct values – in this case, boolean True and False - but many occurrences of those values. This would happen if, for example, you had data on whether or not each resident in a city has internet access. Bitmap indexes use bit arrays (commonly called bitmaps) and answer queries by performing bitwise logical operations on these bitmaps. Bitmap indexes have a significant space and performance advantage over other structures for query of such data. Their drawback is they are less efficient than the traditional B-tree indexes for columns whose data is frequently updated: consequently, they are more often employed in read-only systems that are specialized for fast query - e.g., data warehouses, and generally unsuitable for online transaction processing applications. However, this drawback appears to apply only to their implementation in relational database management systems: certain non-relational DBMSs, notably Intersystems Cache, a hierarchical database, use bitmap indexes for low-cardinality columns in transactional systems.

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