BG: A scalable benchmark for interactive social networking actions

To rate the fastest data stores, BG scales both vertically and horizontally, generating a higher number of requests per second as a function of additional CPU cores and nodes. This is realized using a shared-nothing architecture in combination with two multi-node execution paradigms named Integrated DataBase (IDB) and Disjoint DataBase (D2B). An evaluation of these paradigms shows the following tradeoffs. While the D2B scales superlinearly as a function of nodes, it may not evaluate data stores that employ client-side caching objectively. IDB provides two alternative execution paradigms, Retain and Delegate, that might be more appropriate. However, they fail to scale as effectively as D2B. We show elements of these two paradigms can be combined to realize a hybrid framework that scales almost as effectively as D2B while exercising the capabilities of certain classes of data stores as objectively as IDB.