Answer / a.jyothsna

In a bitmap index, a bitmap for each key value is used
instead of a list of rowids.
Each bit in the bitmap corresponds to a possible rowid. If
the bit is set, then it means that the row with the
corresponding rowid contains the key value. A mapping
function converts the bit position to an actual rowid, so
the bitmap index provides the same functionality as a
regular index even though it uses a different
representation internally. If the number of different key
values is small, then bitmap indexes are very space
efficient. Bitmap indexing is of great benefit to data
warehousing applications.

Answer / satendra

Bit map Indexes are used with the columns having low
cardianality like Gender(M/F),Marital Status.The benefit of
it is that it requires a small space comapred to the case
if a B-Tree index is created on the same column of the
table.
Bit map Indexes are useful in the systems where data is not
getting updated frequently.

Answer / pinkey

Bitmap indexes are widely used in data warehousing
environments. The environments typically have large amounts
of data and ad hoc queries, but a low level of concurrent
DML transactions. For such applications, bitmap indexing
provides:

Reduced response time for large classes of ad hoc queries
Reduced storage requirements compared to other indexing
techniques
Dramatic performance gains even on hardware with a
relatively small number of CPUs or a small amount of memory
Efficient maintenance during parallel DML and loads

Answer / 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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