Multi-tenant DBMSs are used by Cloud providers for their DBaaS (Database-as-a-Service) products. They could be Single-node RDBMSs installed in VMs, SQL-on-Hadoop systems running on a cluster, or parallel RDBMSs with a shared-nothing or shareddisk architecture. From a Cloud provider's point of view, it is interesting to measure these systems' capability of dealing with multi-tenant workloads. From a tenant's point of view, having the above information on different providers could be helpful in choosing the most suitable one (or several for a multi-cloud deployment). In this paper, we present MTD-DS benchmark (with MTD for Multi-Tenant parallel DBMSs and DS for Decision Support), which extends TPC-DS by adding a multitenant query workload generator, a performance SLO (Service Level Objective) generator, configurable DBaaS pricing models, and new metrics to measure the potential capability of a multitenant parallel DBMS in obtaining the best trade-off between the provider's benefit and the tenants' satisfaction. Example experimental results have been produced to show the relevance and the feasibility of the MTD-DS benchmark.