Massive individuals identification is a challenging problem in modern society. Particularly, finger-vein recognition is an emerging biometric technique with several advantages, especially in terms of security against forgery. In this paper, we propose a hybrid parallel matching process for finger-vein recognition under two different parallel platforms, by using the Local Line Binary Pattern descriptor and Hamming distance. Our proposal aims to reduce the computation time of the matching process for massive individuals identification by using finger-vein patterns. Extensive evaluation shows that our approach obtains a high speed-up under a multi-core platform and a close to linear behavior for a multi-node platform. The results with our hybrid parallel system show that it is suitable for real-time individuals identification, achieving a speed-up up to 129.98x. To the best of our knowledge, our work is the first implementation of finger-vein recognition under a parallel platform, which is the main contribution of this paper.