Code in this repository is based on Google's B-tree implementation.

C++ B-tree is a template library that implements ordered in-memory containers based on a B-tree data structure. Similar to the STL std::map, std::set, std::multimap, and std::multiset templates, this library provides btree::map, btree::set, btree::multimap and btree::multiset.

This difers from the original project by Google in that containers behave more like modern STL (C++17) and are an almost drop-in replacements (except for the iterator invalidation, see below); including support for emplace and try_emplace as well as values in the map not needing to have a default constructor.

C++ B-tree containers have a few advantages compared with the standard containers, which are typically implemented using Red-Black trees. Nodes in a Red-Black tree require three pointers per entry (plus 1 bit), whereas B-trees on average make use of fewer than one pointer per entry, leading to significant memory savings. For example, a set<int32_t> has an overhead of 16 bytes for every 4 byte set element (on a 32-bit operating system); the corresponding btree::set<int32_t> has an overhead of around 1 byte per set element.

B-trees are widely known as data structures for secondary storage, because they keep disk seeks to a minimum. For an in-memory data structure, the same property yields a performance boost by keeping cache-line misses to a minimum. C++ B-tree containers make better use of the cache by performing multiple key-comparisons per node when searching the tree. Although B-tree algorithms are more complex, compared with the Red-Black tree algorithms, the improvement in cache behavior may account for a significant speedup in accessing large containers.

The C++ B-tree containers are not without drawbacks, however. Unlike the standard STL containers, modifying a C++ B-tree container invalidates all outstanding iterators on that container.