Processing large volumes of RDF data requires sophisticated tools. In recent years, much effort was spent on optimizing native RDF stores and on repurposing relational query engines for large-scale RDF processing. Concurrently, a number of new data management systems---regrouped under the NoSQL (for ``not only SQL'') umbrella---rapidly rose to prominence and represent today a popular alternative to classical databases. Though NoSQL systems are increasingly used to manage RDF data, it is still difficult to grasp their key advantages and drawbacks in this context. This work is, to the best of our knowledge, the first systematic attempt at characterizing and comparing NoSQL stores for RDF processing. In the following, we describe four different NoSQL stores and compare their key characteristics when running standard RDF benchmarks on a popular cloud infrastructure using both single-machine and distributed deployments.
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