For traditional data warehouses, mostly large and expensive server and storage systems are used. In particular, for small- and medium size companies, it is often too expensive to run or rent such systems. This problem stems from the use of a) complex cube structures containing pre-aggregated values for reporting and b) materialized views to pre-compute joins between fact and dimensions tables. The inherent design principles of memory-based column databases allow for the computation of aggregations and joins on-the-fly without relying on materialized views, making them the technology of choice for SME analytics. SMEs might, however, need analytical services only from time to time, for example at the end of a billing period. A solution to overcome these problems is to use Cloud Computing. In the Rock project, we are building an OLAP cluster of analytics databases on the Amazon EC2 cloud. For this purpose we build infrastructure around SAP's in-memory column database TREX to support multi-tenancy, replication, and failover. This project is joint work with SAP and the University of California in Berkeley.