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Its main drawback is that it needs the database triples (subject, predicate, object) represented as paths in a trie, for each of the six orders of subject, predicate, and object. The resulting blowup in space makes most systems disregard LTJ or implement it only partially, which makes their corresponding algorithms non-wco. In this paper we show that, by using compact data structures, it is possible to build an index that at the same time matches the query time performance of the fastest classic wco index, and uses a fraction of the space of non-wco indices (which are much slower). Concretely, we make use of compact tree representations to store functional tries using one bit per trie edge, instead of one pointer, and further reduce the space by storing partial tries. Our most compact variant uses 5\u20136 times less space than classic wco implementations and 2\u20133 times less than classic non-wco systems. At solving queries, it is on par with the fastest classic wco system, and 30\u201340 times faster than non-wco systems. We further incorporate improved query resolution strategies into\n                    <jats:italic>CompactLTJ<\/jats:italic>\n                    variants, which makes it considerably faster than classic wco systems as well, on queries that do not output too many results. Finally, we show how\n                    <jats:italic>CompactLTJ<\/jats:italic>\n                    can incorporate dynamism without altering its performance, even under very demanding update regimes. 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