I would say use what you are mastering and available for you, K-means or any statistical concepts and methods could be used with different tools and coding languages.
K means is a statistical concept to estimate the variance from the mean on a range of variables. The alternative is to evaluate the exact deviation on a line by line basis, which can be resource intensive on large data sets.
Joan, there are other alternatives to K-Means: DBSCAN, K-Harmonic, Fuzzy K-Means.., but sincerely I am not used to those.
Joan, you may use an open source tool called Gephi (https://gephi.org/users/download/) for clustering. It provides different algorithms and methods for clustering and can deal with large amounts of data. Cheers
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