Upgrade, extend or replace?

The B-eye Network has recently conducted a survey on behalf of
Dataupia which asked, amongst other things, companies whether they
would consider a “rip and replace” approach to solving whatever
data warehousing problems they might have. 75% of respondents said
no.

Now, apart from the fact that I find the term “rip and replace”
pejorative this raises some interesting points. The first is that I
find 75% surprisingly low. It suggests that fully a quarter of all
organisations are so fed up with the problems and costs associated
with their current solutions (if “solution” is the right word for
something that is obviously failing to deliver) that they are
prepared to go through all the upheaval of ripping out and
replacing their current systems.

However, it is not on this aspect that I want to focus but
rather on the 75% who are loyal, or potentially loyal, to their
existing data warehouse supplier. Now, we must suppose that there
are some such customers that are happy with their current lot: they
haven’t got increasing data volumes, are happy with the amount of
data that is currently archived to tape that can’t be queried, they
don’t have any demand to embed business intelligence capabilities
into operational applications, the performance of their queries is
so fast that they get returned within the blink of an eye, they
have no concerns over the ease and cost of administration of the
existing system, there are no additional users that want to be able
to use the warehouse and there is no requirement for supporting
unpredictable or complex queries that might overturn the
performance applecart.

Yes, right.

Well, leaving them aside, what can any normal company, which has
exactly these sorts of issues, do? If replacing the existing system
with something bigger (or smaller in some instances) and better is
not an option?

Firstly, that depends exactly what your issues are. If your
issue is primarily one of performance then the obvious option is to
add one or more data marts: presumably from a data warehouse
appliance vendor, which is fine though it may mean that your whole
environment becomes more complex.

However, if your issues are more complex; for example, you have
concurrency and data volume issues as well as performance, then
simply adding some new data warehouse appliances is unlikely to
resolve the problem and, given that you don’t want to replace your
existing system, then you are going to have to improve the existing
system in some way.

There are two ways of doing this: either you can upgrade your
existing system through a new version of your supplier’s software
or by upgrading the hardware that it runs on, or you can extend
your existing environment via a third party.

The problem with upgrading the existing environment is that what
you get is more of the same. Certainly, if you upgrade to Oracle
11g, for example, then you can use its compression features to
reduce your storage requirement, and you will get some performance
benefits too. In other words, you will get incremental benefits. In
fact, you may even get significant benefits but what you probably
won’t get is the sort of order of magnitude benefits that you
want.

And it is these companies, who want order of magnitude benefits
but don’t want to rip and replace, that Dataupia is targeting.
Hence its sponsorship of this survey. So, can it deliver on that
promise? Well, it is early days for the company but one of its
first customers, which is using Dataupia in conjunction with an
Oracle database is now loading 3090 days worth of call data records
(it is a telecommunications company) into its warehouse, whereas
previously it only stored them for between 3 and 7 days. And it is
getting the same sort of performance on the expanded system as it
did before. That sounds like an order of magnitude improvement to
me.