During the past few years, with the fast development and proliferation of the Internet of Things (IoT), many application areas have started to exploit this new computing paradigm. The number of active computing devices has been growing at a rapid pace in IoT environments around the world. Consequently, a mechanism to deal with this different devices has become necessary. Middleware systems solutions for IoT have been developed in both research and industrial environments to supply this need. However, device discovery and selection, as well decision analytics remain a critical challenge. In this work we present the Decision Support IoT Framework composed of COBASEN, an IoT search engine to address the research challenge regarding the discovery and selection of IoT devices when large number of devices with overlapping and sometimes redundant functionality are available in IoT middleware systems, and DMS, which allows to set up analytic computations on device data when it is still in motion, extracting valuable information from it for decision management. COBASEN operates based on textual characteristics of devices. The DMS uses Complex Event Processing to analyze and react over streaming data, allowing for example, to triggers an alert when a specific error or condition appears in the stream. The main goal of this work is to highlight the importance of an IoT search engine for devices and a decision support system for stream analytics in the IoT paradigm. We developed two systems that implements COBASEN and DMS concepts. However, for preliminarily tests, we made a functional evaluation of both systems in terms of performance. Our initial findings suggest that the Decision Support IoT Framework provides important approaches that facilitate the development of IoT applications, which may perform essential roles to improve IoT processes.