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The RDF Stream Processing (RSP) is gaining momentum. The RDF stream data model is progressively adopted and many SPARQL extensions for continuous querying are converging to a unified RSP query language. However, the RSP community still has to investigate when transforming data streams in RDF streams pays off. In this paper, we report on several experiments on a revolutionized version of our Streaming Linked Data framework (namely, SLD Revolution). SLD Revolution (i) operates on time-stamped generic data items (events, tuples, trees and graphs), and (ii) it applies a lazy-transformation approach, i.e. it processes data according to their nature as long as possible. SLD Revolution results to be a cheaper (it uses less memory and has a smaller CPU load), faster (it reaches higher maximum input throughput), yet more accurate (it provides a smaller error rate in the results) solution than its …