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From Jack Krupansky <>
Subject Re: Cassandra Ussages
Date Tue, 01 Mar 2016 16:34:13 GMT
OLAP using Cassandra and Spark:

What is the cardinality of your cube dimenstions? Obviously any
multi-dimensional data must be flattened.

Cassandra tables have fixed named columns, but... the map datatype with
string key values effectively gives you extensible columns.

-- Jack Krupansky

On Tue, Mar 1, 2016 at 11:22 AM, Andrés Ivaldi <> wrote:

> Jonathan thanks for the link,
> I believe that maybe is good as Data Store part, because is fast for I/o
> and handles Time Series, for analytics could be with Apache Ignite and/or
> Apache Spark
> what it worries me is that looks very complex create the structure for
> each Fact table and then extend
> regards.
> On Sun, Feb 28, 2016 at 12:28 PM, Jonathan Haddad <>
> wrote:
>> Cassandra is primarily used as an OLTP database, not analytics. You
>> should watch this 30 min video discussing Cassandra core concepts (coming
>> from a relational background):
>> On Sun, Feb 28, 2016 at 5:40 AM Andrés Ivaldi <> wrote:
>>> Hello, At my work we are looking for new technologies for an Analysis
>>> Engine, and we are evaluating differents technologies one of them is
>>> Cassandra as our Data repository.
>>> Now we can execute query analysis agains an OLAP Cube and RDBMS, using
>>> MSSQL as our data repository. Cube is obsolete and SQL server engine is
>>> slow as data repository.
>>> I don't know much about cassandra, I read some books, and looks to fit
>>> well on what we are needing, but there are some things that looks like a
>>> problem for us.
>>> Our engine is designed to be scalable, flexible and dynamic, any user
>>> can add new dimensions or measures from any source, all the data is stored
>>> on Cube(this is fixed data) and MSSQL(dynamic data) so we have decoupled
>>> tables with the dimension values.
>>> Ok, with the context given I'll like to clear some doubts
>>> - I able to flat the table with all the possible dimension values to
>>> cassandra, creating the pk against the dimension columns? this will give me
>>> the "sensation" of data pivot over the PK columns? If correct, what if I
>>> want to select the order of the columns, or add another or reduce them?
>>> - It's possible to extend the values of a row dynamically? What we do
>>> often is join row against a value of a mapped external data value to extend
>>> the dimensions hierarchical value structure (ie state->Country->Continent)
>>> I know we can do some of this things in the core of our engine, like the
>>> dimension extension of the values or reduce columns, but as we are
>>> evaluating differents technologies is good to know.
>>> Regards!!
>>> --
>>> Ing. Ivaldi Andres
> --
> Ing. Ivaldi Andres

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