With CArrays you can only have one specific type for the array (int,
float, etc) whereas with a table each column can have a different type
(string, float, etc). If you want to replicate this with carray, you
would have to have multiple carray's for each type.
I think for storing numerical data where querying isn't that
important, carrays are just fine.
But even if you have to query, you can replicate the indexing behavior
for example by adding a second carray with the values you want to
index.



On Mon, Sep 24, 2012 at 3:27 PM, Luke Lee <durdenm...@gmail.com> wrote:
> Thanks for the information guys.  I have joined the dev group on Google
> groups.  I'm sure I can learn a lot just by watching the discussions.
>
> Also, I think for my current situation I'm going to stick with Pytables
> carrays.  We already have Pytables as a dependency, and we are using it for
> some other stuff in the project as well.  I will definitely keep the
> stand-alone carray project in mind for the future though.
>
> I guess by using Pytables.carrays I'm just losing the ability to query,
> etc.?  Are there any other downsides in a Pytables.carray vs. Pytables.table
> comparison?
>
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