With large computing systems, traces are getting bigger and bigger and their analysis needs to scale accordingly. Trace analysis mainly necessitates deriving state information from trace events. These states need to be saved and displayed to the user at different zoom levels. With larger traces containing billions of events, an efficient framework is necessary to be able to move in time and display this information. Trace Compass is a trace analysis framework that is sufficiently modular so that different state stores can be tested on different trace formats. We developed two additional state storing mechanism in Trace Compass and compared it to the one currently used. In this presentation, we will analyze these implementations and show their scalability against different trace samples (GPU traces, kernel traces, function entry/exit traces).