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PDF-search vs Devonthink vs Foxtrot vs Devonsphere

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Posted by MadaboutDana
Jul 20, 2021 at 07:40 AM


Yes, I haven’t really used my copy of PDF Search very much, because I use FoxTrot almost exclusively, but it’s a very powerful search engine.

Reminds me I must dig it out and give it another go!


Posted by Dellu
Jul 20, 2021 at 08:02 AM


PDF-search seems to create much bigger database.

My collection of pdf files about 11.8 GB in finder.

That turn out to be just 797mb in Foxtrot`s index.
Just putting the same folder, PDF-search already piled up 9GB database. it seems like PDF-search copies the whole thing; while Foxtro does some magic.


Posted by MadaboutDana
Jul 20, 2021 at 02:03 PM


@dellu – yes, I remember finding the same thing. FoxTrot extracts all text to generate its indices (and that’s the basis of the FoxTrot mobile app for iOS; it uses the text-based indices, not the actual files, although you can transfer the actual files if you want to and have enough storage space on your iOS/iPadOS device).

Whereas PDF Search, well, clearly doesn’t!


Posted by Simon
Jul 20, 2021 at 07:41 PM


I’ve used all 3. Foxtrot (and again, this is the Pro version), just works and is powerful. It’s also crazy fast. The only caveat for me is that it doesn’t seem to do so well with emails (I have 85K emails). For this reason I have Devonthink Pro. However, Devonthink is slow in opening and if I were using it constantly, there are too many beachballs. A tremendous positive with Devonthink is if you also want you data on iOS. You can do this with Foxtrot, but it’s not so elegant. DevonSPHERE left me all meh.


Posted by Dellu
Jul 21, 2021 at 02:58 PM


After experimenting with pDF-search for a while, I find it pretty fascinating. The results in PDF-search are much more surprising, than the ones I find in Foxtrot or Devonthink. The reason might be because it uses compilations of algorithms,  to rank the pages.

>PDF Search algorithm calculates a rank value for every page in documents according to keywords you entered. These ranks are computed as follows:.
>Keyword Distance : Pages containing keywords nearer to each other have a higher rank.
>Keyword Density : Pages containing more keywords have a higher rank.
>Importance : Pages that contain the keywords in the title or that are rendered in bold or a larger font will have a higher rank.
>Document Date: Pages within more recent files are ranked more highly than older files.



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