SAP Event Stream Processor (ESP) platform aims at delivering real-Time stream processing and analytics in many time-critical areas such as Capital Markets, Internet of Things (IoT) and Data Center Intelligence. SAP ESP allows users to realize complex event processing (CEP) in the form of pattern queries. In this paper, we present MOTTO -A multi-query optimizer in SAP ESP in order to improve the performance of many concurrent pattern queries. This is motivated by the observations that many real-world applications usually have concurrent pattern queries working on the same data streams, leading to tremendous sharing opportunities among queries. In MOTTO, we leverage three major sharing techniques, namely merge, decomposition and operator transformation sharing, to reduce redundant computation among pattern queries. In addition, MOTTO supports nested pattern queries as well as pattern queries with different window sizes. The experiments demonstrate the efficiency of the MOTTO with real-world application scenarios and sensitivity studies.