Database diversity

Discussion of choices and variety in database management system architecture. Related subjects include:

July 5, 2011

Eight kinds of analytic database (Part 2)

In Part 1 of this two-part series, I outlined four variants on the traditional enterprise data warehouse/data mart dichotomy, and suggested what kinds of DBMS products you might use for each. In Part 2 I’ll cover four more kinds of analytic database — even newer, for the most part, with a use case/product short list match that is even less clear.  Read more

July 5, 2011

Eight kinds of analytic database (Part 1)

Analytic data management technology has blossomed, leading to many questions along the lines of “So which products should I use for which category of problem?” The old EDW/data mart dichotomy is hopelessly outdated for that purpose, and adding a third category for “big data” is little help.

Let’s try eight categories instead. While no categorization is ever perfect, these each have at least some degree of technical homogeneity. Figuring out which types of analytic database you have or need — and in most cases you’ll need several — is a great early step in your analytic technology planning.  Read more

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

October 11, 2010

NoSQL overview

My NoSQL article is finally posted; I hope it lives up to all the foreshadowing. It is being run online at Intelligent Enterprise/Information Week, as per the link above, where Doug Henschen edited it with an admirably light touch.

Below please find three excerpts* that convey the essence of my thinking on NoSQL. For much more detail, please see the article itself.

*Notwithstanding my admiration for Doug’s editing, the excerpts are taken from my final pre-editing submission, not from the published article itself.

My quasi-definition of “NoSQL” wound up being:  Read more

October 10, 2010

Partnering with Cloudera

After I criticized the marketing of the Aster/Cloudera partnership, my clients at Aster Data and Cloudera ganged up on me and tried to persuade me I was wrong. Be that as it may, that conversation and others were helpful to me in understanding the core thesis:  Read more

April 12, 2010

Is the enterprise data warehouse a myth?

An enterprise data warehouse should:

Pick ONE. Read more

March 13, 2010

The Naming of the Foo

Let’s start from some reasonable premises. Read more

January 17, 2010

Three broad categories of data

People often try to draw a distinction between:

There are plenty of problems with these formulations, not the least of which is that the supposedly “unstructured” data is the kind that actually tends to have interesting internal structures. But of the many reasons why these distinctions don’t tend to work very well, I think the most important one is that:

Databases shouldn’t be divided into just two categories. Even as a rough-cut approximation, they should be divided into three, namely:

Even that trichotomy is grossly oversimplified, for reasons such as:

But at least as a starting point, I think this basic categorization has some value. Read more

December 12, 2009

The legit part of the NoSQL idea

I’ve written some snarky things about the “NoSQL” concept – or at least the moniker. (Carl Olofson’s term “non-schematic databases” seems less bad.) Yet I’m actually favorable about the increasing use of SQL alternatives. Perhaps I should pull those thoughts together. Read more

December 11, 2009

NoSQL Q and A

Neal Leavitt is writing an article for IEEE on NoSQL. So he’s circulated a long list of questions, encouraging people to answer as many or few as they choose. Unfortunately, most of the questions are technically meaningless, in that they implicitly rely on the false assumption that there is such a thing as a single or at least reasonably well-defined NoSQL technology. (I imagine most of his questions are really about key-value stores.) Nonetheless, I took a crack at a number of them before getting bored. Anybody else want to pitch in too? Read more

← Previous PageNext Page →

Feed: DBMS (database management system), DW (data warehousing), BI (business intelligence), and analytics technology Subscribe to the Monash Research feed via RSS or email:


Search our blogs and white papers

Monash Research blogs

User consulting

Building a short list? Refining your strategic plan? We can help.

Vendor advisory

We tell vendors what's happening -- and, more important, what they should do about it.

Monash Research highlights

Learn about white papers, webcasts, and blog highlights, by RSS or email.