With the recent explosive growth of data in the real world, data mining techniques to obtain characteristics and knowledge from big data attract more attention. This paper focuses on a method to detect outliers in streaming data, and proposes a fast FPGA implementation of outlier detection based on the Mahalanobis distance. The proposed circuit is fully pipelined, and in every clock cycle, a given sample data can be judged as an outlier or not. Experimental evaluation shows that the proposed circuit is 37 times faster than the software implementation of the Mahalanobis distance-based outlier detection.