Cubes Superset Integration

[Christian Ledermann]

I'd like to pitch an idea:

Superset and Cubes have complementary goals, while Superset is focused on  Presentation 

Cubes provides the underlying Model and View layer.

# What is Cubes (in a nutshell)?

Cubes is a light-weight Python framework and set of tools for Online Analytical Processing (OLAP),

multidimensional analysis and browsing of aggregated data. Focus on data analysis, in human way.

Purpose is to provide a framework for giving analyst or any application end-user understandable 

and natural way of presenting the multidimensional data. 

One of the main features is the logical model, 

which serves as abstraction over physical data to provide end-user layer.

Features:

  - OLAP and aggregated browsing (default backend is for relational databse - ROLAP)

  - multidimensional analysis

  - logical view of analysed data - how analysts look at data, how they think of data, 

    not not how the data are physically implemented in the data stores

  - hierarchical dimensions (attributes that have hierarchical dependencies, 

    such as category-subcategory or country-region)

  - localizable metadata and data

  - SQL query generator for multidimensional aggregation queries

  - OLAP server – HTTP server based on Flask Blueprint, 

    can be easily integrated into your application.

# Why Cubes for Superset?

Currently Superset does only support OLAP Cubes on top of Druid.io and `raw SQLAlchemy`.

# What would be the advantages for Cubes?

  - An out of the box powerful visualization solution.

  - Access to the huge and growing Superset community

  - Increased visibility which may attract more contributors to cubes

  

  

# What are the advantages for Superset?

  - access to an opensource lightweight (R)OLAP server built in python 

    (which seems an ideal match as Superset itself is built in python)

  - support OLAP out of the box without the need for Druid.io

  

  

# Where to start an integration?

In https://github.com/airbnb/superset/tree/master/superset/connectors

are examples for Druid and SqlAlchemy connectors. 

Superset Connectors seem a to be good match to be built with Expressions 

(https://github.com/DataBrewery/expressions)

[Maxime Beauchemin]

Hi Christian,

In a previous life (<= 2007) I was a MS SSAS, Hyperion Essbase and MDX expert, so I have context on the OLAP topic.

I have to dig into more of the specific of the "Cubes" python package and how exactly it fits with Superset but conceptually that seems like a great good idea. I'll post back here after reading through the docs.

Christian, are you the lead maintainer of Cubes?

Max

[Christian Ledermann]

On 24 May 2017 at 18:09, Maxime Beauchemin <maximebe...@gmail.com> wrote:
> Hi Christian,
>
> In a previous life (<= 2007) I was a MS SSAS, Hyperion Essbase and MDX
> expert, so I have context on the OLAP topic.
>
> I have to dig into more of the specific of the "Cubes" python package and
> how exactly it fits with Superset but conceptually that seems like a great
> good idea. I'll post back here after reading through the docs.
>
> Christian, are you the lead maintainer of Cubes?

No, but we will use Cubes and/or Superset in the future

I was evaluating analytics options for our internal data and evaluated
Cubes and Superset.
(as well as other open source and commercial options)

You an already use cubes together with superset by denormalizing the cubes:
http://pythonhosted.org/cubes/slicer.html#denormalize

I see this rather as an interim solution and try to drum up some collaborators
(from both sides) for a 'native' integration as i will not have the
time to tackle
this any time soon.

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--
Best Regards,

Christian Ledermann

Newark-on-Trent - UK
Mobile : +44 7474997517

https://uk.linkedin.com/in/christianledermann
https://github.com/cleder/


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