With the increase of the number of motor vehicles and vehicle traffic in the city, the phenomenon of fake plate vehicle appears repeatedly. In order to solve the problem of fake plate monitoring, the traffic management departments adopt traditional identification methods, such as manual identification, license plate recognition, radio frequency identification, etc. Nevertheless, facing the massive log records, these methods generally have problems of low efficiency and poor real-time performance. So big data technology was introduced, and fake plate vehicle real-time analysis storage system based on Kafka and Storm was proposed. Kafka can be used as a middleware for caching, improving the synchronization of data collection and data analysis, and avoiding data loss. The Storm framework can realize real-time calculation of log information, and then store the information of the fake plate vehicles in the specified document. The entire system has real-time, distributed storage, stability, scalability, and so on.