1. In-memory OLAP. Classic MOLAP cube loaded entirely in memory.
Vendors: IBM Cognos TM1, Actuate BIRT
Pros:
- Fast reporting, querying and analysis, because the entire model and data are all in memory
- Ability to write back
- Accessible by 3rd party MDX tools (IBM Cognos TM1 specifically)
Cons:
- Requires traditional multidimensional data modeling.
- Limited to single physical memory space (theoretical limit of 3TB, but we haven’t seen production implementations of more than 300GB – this applies to the other in-memory solutions as well)
2. In-memory ROLAP. ROLAP metadata loaded entirely in memory.
Vendors: MicroStrategy
Pros:
- Speeds up reporting, querying and analysis, because metadata is all in memory
- Not limited by physical memory
Cons:
- Only metadata, not entire data model is in memory, although MicroStrategy can build complete cubes from the subset of data held entirely in memory
- Requires traditional multidimensional data modeling
3. In-memory inverted index. Index (with data) loaded into memory.
Vendors: SAP BusinessObjects (BI Accelerator), Endeca
Pros:
- Fast reporting, querying and analysis, because the entire index is in memory
- Less modelling required than an OLAP-based solution
Cons:
- Limited by physical memory
- Some index modelling still required
- Reporting and analysis limited to entity relationships built in index
4. In-memory associative index. An array/index with every entity/attribute correlated to every other entity/attribute.
Vendors: QlikView, TIBCO Spotfire, Advizor Solutions (also OEMd by Information Builders)
Pros:
- Fast reporting, querying and analysis, because the entire index is in memory
- Less modelling required than an OLAP based solution
- Reporting, querying, analysis can be done without any model constraints, for example any attribute can be instantly reused as fact or as a dimension. Every query with an inner-join can also show results of an outer join on every column.
Cons:
- Limited by physical memory
- Some scripting/modelling still required to load the data
5. In-memory spreadsheet. Spreadsheet like array loaded entirely into memory.
Vendors: Microsoft (PowerPivot)
Pros:
- Fast reporting, querying and analysis, because the entire spreadsheet is in memory
- No modelling required
- Reporting and analysis are as simple as sorting and filtering a spreadsheet
Cons:
- Limited by physical memory
What did I miss and what did I get wrong - comments?
Boris also blogs at http://blogs.forrester.com/boris_evelson/.
