If you’re been tasked with implementing or supplementing business intelligence offerings in your organization lately (read: a data mart, for example), the choices have gotten quite a bit more complicated. A while ago, you would have your pick of three or four vendors. If one of those vendors was already in-house handling your transactional systems, guess what, he was likely to also handle your warehousing needs. Or at least try to.
Nowadays, the decision path is a little more involved because the BI world is no longer ruled by a small oligarchy (namely Oracle, Microsoft and IBM). The proliferation of “new-breed” analytical engine vendors has greatly expanded a buyer’s options. There are around twenty-some players in this field now. Not only that, but delivery options have expanded as well.
Nowadays, you can get BI delivered and running in-house sitting on commodity or custom hardware. You can buy canned appliances. You can go proprietary bits. You can go Open Source. Or you can tap the “cloud” with an on-demand subscription-based model. You can pick a columnar vendor, or a row-based one. You can choose an MPP architecture, or an SMP implementation. You can even stick with the “gorillas” if that makes you feel better (and money is no object). These different paths are all strategically different both technically and economically. The modern BI strategist is compelled to choose wisely in an unforgiving economy where failure is no longer an option (this time they mean it).
So for the sake of argument, I’m going to assume the following buyer profile:
- Money is _definitely_ an object.
- IT resources are non-existent, limited, not available, or not inclined to help.
- A lengthy proof-of-concept (POC) cycle is not an option.
- Project timeline is measured in weeks not months or years.
- C-level people want to see incremental results starting today.
- A single DBA is left standing in your organization (but next week, maybe zero).
- Your ass is on the line.
I think this describes a fairly common scenario these days. Faced with such odds, I think most people opt for the path of least economic and implementation resistance. Most people don’t have $2-6M hanging around including staff and a six-twelve month window to implement a full-blown Oracle, Microsoft or IBM solution. These days are simply gone (good riddance on that). It would appear at first glance that the only remaining alternatives would be open source (OSS) or on-demand SaaS software.
Now, OSS is attractive from a cost basis, as most freebies tend to be. Yes, you do pay for support if pulling down “enterprise” versions of the software but in many cases, some buyers get away using the free versions for a while, at least for quick POCs. In some cases, the free versions are either limited or incomplete in functionality (like InfoBright, for example) so that could be a “gotcha” depending on your application needs. Similarly, non-enterprise versions usually depend on community for support. If you’re in a jam and need serious dedicated support on a moment’s notice, you’ll need to pony up for an enterprise version or wait until “the community” comes up with an adequate answer to your problem (if ever).
Additionally, OSS does have hidden costs, not the least of which are installation, setup, configuration, and maintenance. But, if you happen to be a Linux shop and have enough LAMP developers on staff with sufficient expertise and time, and your management happens to be accepting of the whole OSS concept, it might just be a viable option.
Another quick way to get up and running quickly is to go the Cloud (SaaS) service route. In that scenario, you pay a monthly fee to access a BI platform in the cloud. This hands-off approach is certainly attractive in many cases provided data volumes and security restrictions do not get in the way. Shlepping 10-100TB of data offsite is not something most people consider yet. But, for smaller data sizes, SaaS is certainly an option. Vertica, Kognitio and Aster Data come to mind as the latest new-breeders to provide cloud-based services to customers (either on proprietary or public cloud platforms like EC2). There is a flurry of other on-demand BI players as described in several of my past posts. Of course, the downsides there tend to be upload time, limited functionality and vendor lock-in.
Now if I can get on my soapbox for a minute, I’m going to pitch a third option. At XSPRADA, we’ve developed a 5MB high-performance analytical database running as a Windows service on commodity hardware and Server 2003 or 2008 x64 operating systems. You can install this puppy internally (your data stays nice and safe in-house) in about 2.5 minutes including ODBC drivers. You then point it at your CSV data on disk and start firing off queries immediately. The more you ask, the faster it gets. And you can show results in minutes, not weeks or months. No cubing, no indexing, no pre-structuring, no partitioning, none of that nonsense. That’s the bottom line in a nutshell. I promise you business intelligence is not the rocket science so many folks make it out to be! For those who might be hesitating between open source, SaaS or much more expensive in-house solutions, I think this is a pretty unique proposition. There really is nothing like it anywhere else on the market, and it just so happens we have a 30 day trial going on right now if you visit our website J