A Boost B-tree library would provide disk-based associative containers that scale all the way from really, really, small to really, really, large. B-trees perform well on hardware ranging from ancient floppy disk drives all the way up to humongous disk arrays. They are the technology behind most high-performance disk file systems and databases. If you don't know what a B-tree is, or think that "B-tree" is an abbreviation for "Binary tree", you might want to read the Wikipedia B-Tree article: http://en.wikipedia.org/wiki/B-tree. Knuth and other computer science texts also supply descriptions. See http://mysite.verizon.net/beman/btree/index.html for a more complete description of the proposed library. A preliminary implementation is available. Download http://mysite.verizon.net/beman/btree/btree-preview-1.zip, and unpack into a current Boost distribution. A few existing Jamfiles will be overwritten. The only compilers tested and working so far are VC++ 10 and GCC/MinGW 4.5. You can view the library online at http://github.com/Beman/Boost-Btree There is no detailed documentation yet, but if you know how to use std::map and other standard library associative containers, you already know most of what you need to know. Critical differences are documented in the Library Characteristics section of the index.html page referenced above. Initial timing tests have been very encouraging. The time test compares the btree_map implementation to std::map. As expected, a btree_map is many times slower than a std::map, given a cold operating system file cache and constraining the btree_map's caching to a minimum. But at the other extreme, when the O/S file cache is warm and the btree_map's cache is as large as the file, the btree_map is very similar in speed to std::map.The btree library's code is still very new, so timings and everything else may be subject to lots of revision. Any interest? --Beman