In this chapter we discuss various bitmap index technologies for efficient query processing in data warehousing applications. We review the existing literature and organize the technology into three categories, namely bitmap encoding, compression and binning. We introduce an efficient bitmap compression algorithm and examine the space and time complexity of the compressed bitmap index on large data sets from real applications. According to the conventional wisdom, bitmap indices are only efficient for low-cardinality attributes. However, we show that the compressed bitmap indices are also efficient for high-cardinality attributes. Timing results demonstrate that the bitmap indices significantly outperform the projection index, which is often considered to be the most efficient access method for multi-dimensional queries. Finally, we review the bitmap index technology currently supported by commonly used commercial database systems and discuss open issues for future research and development.