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I've played with a wide variety of these sorts of databases over the years, here are some impressions- (well, I don't -do- impressions, I'm a scientist...)
A few things to note -- I do vision research, I use TeX / BibTeX, many new reprints I use are available from PubMed-indexed sources, I've scanned in and OCRd a few thousand of my old reprints (with the help of several brave work study undergrads), my entire database is 3k or so papers and about 10GB. Thus, all my opinions are colored by these facts.
Interesting, but not really geared for scientific papers (ie- no way to associate citation information w/ them easily). Not sure it would handle my entire library. Seems a bit more for the 'here's a bunch of paper I want to digitize' crowd, and for that it looks to be excellent. I found the tagging/metadata a little clumsily implemented. Pros- aesthetically nice. Cons- not good if you want citation information.
Pretty, honestly not even in alpha, let alone near release ready. Crashed chronically, lack of ability to locate files where I want them (ie- incomplete preference system). One nice thing - love the 'select some text and look it up in PubMed' feature to fill out the citation information. I'd love to see this in other programs (notably BibDesk). Not totally clear how the BibTeX is/will be implemented. Pros-aesthetically nice, PubMed lookup nice. Cons- boom! bang! They're charging for these pre-betas with a timeout on the 'trial' of 30 days. Has potential to be sure... but need to -see it work- before I'm willing to invest too many papers / $.
Does a lot more than just database your PDFs. Sort of kitchen sinkish, it handles your papers, other media, web pages, tables, etc. It handles several thousand papers easily. The Office version comes with an interesting web-server to access the database from offsite (the search is wicked-fast), and a really fast OCR (esp compared to the pre-acrobat 8 OCR. 8's OCR is -finally- reasonably fast). Again, there's no -obviously straightforward- way to tie in the BibTeX / citation information. There are ways to do it, they just feel a little clunky. The 'find similar' and 'classify' features are really the most useful here. Have a paper on synaptic plasticity and want to find other papers in your collection that are lexically similar? You can 'see also' them using their engine (which works pretty well, but not top notch with such a large database). It uses something seemingly simple to do the matching, maybe just concordance (nothing like LSA, it doesn't look like - when will Apple expose the hooks to the LSA framework in 10.x ? ).
Pros- cool 'similar paper' finder, web server. Cons- showing its age aesthetically, no easy citation information linkage, have to go through acrobatics to get Spotlight to index PDFs when they're embedded in the database (ie- no good spotlight support).
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