Against the backdrop of ever-growing data volumes and trends like the Internet of Things (IoT) or Industry 4.0, Data Stream Processing Systems (DSPSs) or data stream processing architectures in general receive a greater interest. Continuously analyzing streams of data allows immediate responses to environmental changes. A challenging task in that context is assessing and comparing data stream processing architectures in order to identify the most suitable one for certain settings. The present paper provides an overview about performance benchmarks that can be used for analyzing data stream processing applications. By describing shortcomings of these benchmarks, the need for a new application benchmark in this area, especially for a benchmark covering enterprise architectures, is highlighted. A key role in such an enterprise context is the combination of streaming data and business data, which is barely covered in current data stream processing benchmarks. Furthermore, first ideas towards the development of a solution, i.e., a new application benchmark that is able to fill the existing gap, are depicted.