Hi,

First, happy new year to you all and thanks for the great work on 
SQLAlchemy.

I just would like to share a bit of news. Cubes – Python Lightweight OLAP 
framework is approaching 1.0 with quite a few new things. Cubes is using 
SQLAlchemy for the SQL ROLAP backend. The notable SQL related changes are:

* multiple data stores[1] (databases/connections) per server session
* outer joins for dimensions [2] – allows you to include dimension members 
in the result even if there are no related facts.
* named model-wide join specification – you can specify a join (dimension 
table, column, type, ...) once in the model to be easily reused in any cube 
just by adding cube-specific attribute (just fact key(s))

The "outer joins" feature required a major rewrite of the SQL star schema 
browser. The nature of SQLAlchemy helped a lot.

Some notable non-SQL related changes:

* distinction between measures and aggregates
* new backends: Mongo, Mixpanel, Google Analytics, Slicer

More extensive list of 1.0 changes can be found at [3]

Note: There are many necessary backward incompatible changes. Please refer 
to the documentation for more information.

Links:

[1] http://cubes.databrewery.org/dev/doc/workspace.html
[2] http://cubes.databrewery.org/dev/doc/backends/sql.html#sql-outer-joins
[3] http://cubes.databrewery.org/dev/doc/releases/1.0.html

Comments, bug reports and questions are welcome. The Cubes Goggle Group 
is: https://groups.google.com/forum/#!forum/cubes-discuss

Cheers,

Stefan

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