MOLAP

Analysis of MOLAP (Multidimensional OnLine Analytic Processing) products and vendors. Related subjects include:

May 29, 2011

When it’s still best to use a relational DBMS

There are plenty of viable alternatives to relational database management systems. For short-request processing, both document stores and fully object-oriented DBMS can make sense. Text search engines have an important role to play. E. F. “Ted” Codd himself once suggested that relational DBMS weren’t best for analytics.* Analysis of machine-generated log data doesn’t always have a naturally relational aspect. And I could go on with more examples yet.

*Actually, he didn’t admit that what he was advocating was a different kind of DBMS, namely a MOLAP one — but he was. And he was wrong anyway about the necessity for MOLAP. But let’s overlook those details. 🙂

Nonetheless, relational DBMS dominate the market. As I see it, the reasons for relational dominance cluster into four areas (which of course overlap):

Generally speaking, I find the reasons for sticking with relational technology compelling in cases such as:  Read more

December 28, 2010

Evolving definitions and technology categories for 2011

It seems my prediction of a limited blogging schedule in December came emphatically true. I shall re-start with a collection of quick thoughts, clearing the decks for more detailed posts to follow. Read more

December 11, 2009

Ray Wang on SAP

Ray Wang made a terrific post based on SAP’s annual influencer love-in, an event which I no longer attend. Ray believes SAP has been in a “crisis”, and sums up his views as

The Bottom Line  – SAP’s Turning The Corner

Credit must be given to SAP for charting a new course.  A shift in the management philosophy and product direction will take years to realize, however, its not too late for change.  SAP must remember its roots and become more German and less American.  The renewed focus must put customer requests and priorities ahead of SAP’s bureaucracy.  The emphasis must focus on the relationship.  When that reemerges in how SAP works with customers, partners, influencers, and its own employees, SAP will be back in good graces. In the meantime, its  time to get to work and deliver.  Oracle’s Fusions Apps are coming soon and competitors such as IBM, Microsoft, Epicor, IFS, and SalesForce.com will not relent.

I recall the 1980s, when SAP’s main differentiator, at least in the English-speaking US, was a total commitment to customer success, and when it could be taken for granted that SAP would do business ethically. Things change, and not always for the better.

Anyhow, the reason I’m highlighting Ray’s post is that he makes reference to a number of interesting SAP-cetric technology trends or initiatives. Read more

October 30, 2009

A question on MDX performance

An enterprise user wrote in with a question that boils down to:

What are reasonable MDX performance expectations?

MDX doesn’t come up in my life very much, and I don’t have much intuition about it. E.g., I don’t know whether one can slap an MDX-to-SQL converter on top of a fast analytic RDBMS and go to town. What’s more, I’m heading off on vacation and don’t feel like researching the matter myself in the immediate future. 🙂

So here’s the long form of the question. Any thoughts?

I have a general question on assessing the performance of an OLAP technology using a set of MDX queries. I would be interested to know if there are any benchmark MDX performance tests/results comparing different OLAP technologies (which may be based on different underlying DBMS’s if appropriate) on similar hardware setup, or even comparisons of complete appliance solutions. More generally, I want to determine what performance limits I could reasonably expect on what I think are fairly standard servers.

In my own work, I have set up a star schema model centered on a Fact table of 100 million rows (approx 60 columns), with dimensions ranging in cardinality from 5 to 10,000. In ad hoc analytics, is it expected that any query against such a dataset should return a result within a minute or two (i.e. before a user gets impatient), regardless of whether that query returns 100 cells or 50,000 cells (without relying on any aggregate table or caching mechanism)? Or is that level of performance only expected with a high end massively parallel software/hardware solution? The server specs I’m testing with are: 32-bit 4 core, 4GB RAM, 7.2k RPM SATA drive, running Windows Server 2003; 64-bit 8 core, 32GB RAM, 3 Gb/s SAS drive, running Windows Server 2003 (x64).

I realise that caching of query results and pre-aggregation mechanisms can significantly improve performance, but I’m coming from the viewpoint that in purely exploratory analytics, it is not possible to have all combinations of dimensions calculated in advance, in addition to being maintained.

April 22, 2009

Clearing some of my buffer

I have a large number of posts still in backlog.  For starters, there are ones based on recent visits with Aster, Greenplum, Sybase, Vertica, and a Very Large User.  I suspect I’ll write more soon on Oracle as well.  Plus there’s my whole future-of-online-media area.  And quite a bit more will grow out of planned research.

So there are a whole lot of other worthy subjects I doubt I’ll be getting to any time soon.  In some cases, of course, other people are doing great jobs of writing about same. Here are pointers to a few links that I am glad to recommend:

March 25, 2009

Aleri update

My skeptical remarks on the Aleri/Coral8 merger generated some pushback. Today I actually got around to talking with John Morell, who was marketing chief at Coral8 and has remained with the combined company. First, some quick metrics:

John is sticking by the company line that there will be an integrated Aleri/Coral8 engine in around 12 months, with all the performance optimization of Aleri and flexibility of Coral8, that compiles and runs code from any of the development tools either Aleri or Coral8 now has. While this is a lot faster than, say, the Informix/Illustra or Oracle/IRI Express integrations, John insists that integrating CEP engines is a lot easier. We’ll see.

I focused most of the conversation on Aleri’s forthcoming efforts outside the financial services market. John sees these as being focused around Coral8’s old “Continuous (Business) Intelligence” message, enhanced by Aleri’s Live OLAP. Aleri Live OLAP is an in-memory OLAP engine, real-time/event-driven, fed by CEP. Queries can be submitted via ODBO/MDX today. XMLA is coming. John reports that quite a few Coral8 customers are interested in Live OLAP, and positions the capability as one Coral8 would have had to develop had the company remained independent. Read more

February 7, 2009

Analytics’ role in a frightening economy

I chatted yesterday with the general business side (as opposed to the trading operation) of a household-name brokerage firm, one that’s in no immediate financial peril. It seems their #1 analytic-technology priority right now is changing planning from an annual to a monthly cycle.* That’s a smart idea. While it’s especially important in their business, larger enterprises of all kinds should consider following suit. Read more

February 3, 2009

EMC’s take on data warehousing and BI

I just ran across a December 10 blog post by Chuck Hollis outlining some of EMC’s — or at least Chuck’s — views on data warehousing and business intelligence. It’s worth scanning, a certain “Where you stand depends upon where you sit” flavor to it notwithstanding.  In a contrast to my usual blogging style, Chuck’s post is excerpted at length below, with comments from me interspersed. Read more

January 28, 2009

More Oracle notes

When I went to Oracle in October, the main purpose of the visit was to discuss Exadata. And so my initial post based on the visit was focused accordingly. But there were a number of other interesting points I’ve never gotten around to writing up. Let me now remedy that, at least in part. Read more

September 25, 2008

Other notes on Oracle data warehousing

Obviously, the big news this week is Exadata, and its parallelization or lack thereof. But let’s not forget the rest of Oracle’s data warehousing technology.

  1. Frankly, I’ve come to think that disk-based OLAP cubes and materialized views are both cop-outs, indicative of a relational data warehouse architecture that can’t answer queries quickly enough straight-up. But if you disagree, then you might like Oracle’s new OLAP cube materialized views, which sound like a worthy competitor to Microsoft Analysis Services. (Further confusing things, I’ve seen reports that Oracle is increasing its commitment to Essbase, a separate MOLAP engine. I hope those are incorrect.)
  2. A few weeks ago, I came to realize that Oracle’s data mining database features actually mattered — perhaps not quite as much as Charlie Berger might think, but to say that is to praise with faint damns. 😉 SPSS seems to be getting large performance gains from leveraging the scoring part, and perhaps the transformation part as well. I haven’t focused on getting my details right yet, so I haven’t been writing about it. But heck, with all the other Oracle data warehousing discussion, it seems right to at least mention this part too.

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