From the webpage:
FastBit is an open-source data processing library following the spirit of NoSQL movement. It offers a set of searching functions supported by compressed bitmap indexes. It treats user data in the column-oriented manner similar to well-known database management systems such as Sybase IQ, MonetDB, and Vertica. It is designed to accelerate user’s data selection tasks without imposing undue requirements. In particular, the user data is NOT required to be under the control of FastBit software, which allows the user to continue to use their existing data analysis tools.
The FastBit software is distributed under the Less GNU Public License (LGPL). The software is available at codeforge.lbl.gov. The most recent release is FastBit ibis1.3.7; it comes as a source tar ball named fastbit-ibis1.3.7.tar.gz. The latest development version is available from http://goo.gl/Ho7ty.
Other items of interest:
The most recent entry in this list is 2011. A quick search of the ACM Digital Library (for fastBit) found seventeen (17) articles for 2012 – 2013.
From the users guide:
This package implements a number of different bitmap indexes compressed with Word-Aligned Hybrid code. These indexes differ in their bitmap encoding methods and binning options. The basic bitmap index compressed with WAH has been shown to answer one-dimensional queries in time that is proportional to the number of hits in theory. In a number of performance measurements, WAH compressed indexes were found to be much more efficient than other indexes [CIKM 2001] [SSDBM 2002] [DOLAP 2002]. One of the crucial step in achieving these efficiency is to be able to perform bitwise OR operations on a large compressed bitmaps efficiently without decompression [VLDB 2004]. Numerous other bitmap encodings and binning strategies are implemented in this software package, please refer to indexSpec.html for descriptions on how to access these indexes and refer to our publications for extensive studies on these methods. FastBit was primarily developed to test these techniques for improving compressed bitmap indexes. Even though, it has grown to include a small number other useful data analysis functions, its primary strength is still in having a diversity of efficient compressed bitmap indexes.
Just in case you want to follow up on the use of fastBit in the RaptorDB.