I'm a data scientist with little knowledge of DB technology. I keep hearing 3 types of databases mentioned as key technologies for analytics and modeling solutions:

  • NoSql databases
  • OLAP cubes
  • In-Memory databases

NoSql seems to be anything that isn't relational, so in theory pure OLAP cubes would qualify as NoSql (pure OLAP, not star-schema ROLAP).

But at the same time, I heard a discussion recently by an Oracle engineer about how Oracle spent 2 years trying to convert one of its pure OLAP solutions into NoSql and failed, and that had me confused - if NoSql is anything that is non relational, then it seems to me that pure OLAP is already NoSql, so how can they convert it to NoSql?!?

On a similar note, I hear In-Memory mentioned often as a type of Database that is popular for analytics and modeling solutions, but In-Memory seems to refer to the hardware architecture (using RAM instead of Disk for storage) as opposed to a specific way of representing the data, which seems to me like the key factor in determining whether a database technology is suitable for analytics or not.

So my question is: Are these concepts mutually exclusive or not? Can an OLAP cube be NoSql and in memory as well?

If so, what are some examples?

  • I think you are right that In-Memory is a type of architecture vs database design. OLAP would strike me as structured data, but optimized for reporting, while NoSQL is more of a schema-less (schema in the data) design. – Jonathan Fite Jul 9 '19 at 20:35

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