
Data Brewery – Python Framework for Data Processing - dedalus
http://databrewery.org/
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piroux
I would be interested to know

\- if those projects can be easily used with pandas ...

\- and if some of their features are already in pandas ?

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piroux
anyone ?

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acbart
So is Cubes an interface for Bubbles? I'm having a hard time figuring out the
connection between them.

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stefanu
Author here. They are very independent. In short: Cubes is OLAP framework for
abstracting aggregate queries on top of a datastore, mostly through SQL. You
define a so called multi-dimensional model – how the analysts see the world,
and cubes knows how to project it to underlying data structures, preferably
star or snowflake table schemas.

Bubbles was meant to be data integration library (also known as ETL) – get
data from multiple sources, transform them and produce tables that are more
suitable for further analysis or reporting.

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siddboots
Cubes sounds like what is often called "ROLAP" in the enterprisey analytics
world.

[https://en.wikipedia.org/wiki/ROLAP](https://en.wikipedia.org/wiki/ROLAP)

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Swinx43
I work in the BI space and Cubes is exactly ROLAP.

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haney
It's been a little while since I've seen this, is there still much active
development? Github doesn't show many recent commits.

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stefanu
Author here. I admit, it has been more than a year since I made a significant
contribution. It kind of correlates with change of my job – since I started to
work with my current employer I didn't have almost any time to work on neither
of Data Brewery projects directly. All I have is full notebook of new ideas
and mailbox of unanswered feature requests and bug reports. It makes me sad,
but honestly I don't know how to proceed.

I really enjoyed working on Data Brewery and I eventually will resume my work
as there is a lot to do. It is just put aside on the back burner. In the
meantime I might only hope that someone would volunteer to at least handle bug
fixes. I'm open to grant access to the repositories.

Any suggestion how to prevent open-source project from dying is welcome.

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Swinx43
I am interested to find out what volumes of data each of these solutions,
Cubes and Bubbles, have been tested against?

I work with enterprise tools to create ETL and OLAP solutions daily and really
like what I see here but I am concerned with the performance since it is all
done using Python and performance is not Python's strength.

Do you have any more information regarding this?

