B+-tree has been used as one of the main index structures in a database field fore more than four decades. However, typical B+-tree implementations show scalability and performance issues as modern global-scale Web or mobile applications generate huge volumes of data that has not been seen before. Various key-value storage engines with variants of B+-tree, such as log-structured merge tree (LSM-tree) have been proposed to address these limitations. At Couchbase, we also have been working on a new key-value storage engine that can provide high scalability and performance, and recently released the beta version of ForestDB, whose main index structure is based on Hierarchical B+-Tree based Trie or HB+-Trie. In this presentation, we introduce ForestDB and discuss why ForestDB can be fitted well for modern big data applications. We also explain various optimizations on ForestDB, which are planned especially for solid-state drives (SSDs).