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This paper considers the problem of reasoning on massive amounts of (possiblydistributed) data. Presently, existing proposals show some limitations: {\em(i)} the quantity of data that can be handled contemporarily is limited, due tothe fact that reasoning is generally carried out in main-memory; {\em (ii)} theinteraction with external (and independent) DBMSs is not trivial and, inseveral cases, not allowed at all; {\em (iii)} the efficiency of presentimplementations is still not sufficient for their utilization in complexreasoning tasks involving massive amounts of data. This paper provides acontribution in this setting; it presents a new system, called DLV$^{DB}$,which aims to solve these problems. Moreover, the paper reports the results ofa thorough experimental analysis we have carried out for comparing our systemwith several state-of-the-art systems (both logic and databases) on someclassical deductive problems; the other tested systems are: LDL++, XSB, Smodelsand three top-level commercial DBMSs. DLV$^{DB}$ significantly outperforms eventhe commercial Database Systems on recursive queries. To appear in Theory andPractice of Logic Programming (TPLP)

Experimenting with recursive queries in database and logic programming systems