December 3, 2007
Borrowing the “Fact or fiction?” meme from the sports world:
- Data warehouse appliances have to have specialized hardware. Fiction. Indeed, most contenders except Teradata and Netezza — for example, DATAllegro, Vertica, ParAccel, Greenplum, and Infobright — offer Type 2 appliances. (Dataupia is another exception.)
- Specialized hardware is a dead-end for data warehouse appliances. Fiction. If it were easy for Teradata to replace its specialized switch technology, it would have done so a decade ago. And Netezza’s strategy has a lot of appeal.
- Data warehouse appliances are nothing new, and failed long ago. Fiction, but only because of Teradata. 1980s appliance pioneer Britton-Lee didn’t do so well (it was actually bought by Teradata). IBM and ICL (Britain’s national-champion hardware company) had content-addressable data store technology that went nowhere.
- Since data warehouse appliances failed long ago, they’ll fail now too. Fiction. Shared-nothing MPP is a fundamental advantage of appliances. So are various index-light strategies. Data warehouse appliances are here to stay.
- Data warehouse appliances only make sense if your main database management system can’t handle the job. Fiction. There are dozens of data warehouse appliances managing under 5 terabytes of user data, if not under 1 terabyte. True, some of them are legacy installations, dating back to when Oracle couldn’t handle that much data well itself. But new ones are still going in. Even if Oracle or Microsoft SQL Server can do the job, a data warehouse appliance is often a far superior — cheaper, easier to deploy and keep running, and/or better performing — alternative.
- Data warehouse appliances are just for data marts. For your full enterprise data warehouse, use a conventional DBMS. Part fact, part fiction. It depends on the appliance, and on the complexity of your needs. Teradata systems can do pretty much everything. Netezza and DATAllegro, two of the oldest data warehouse appliance startups, have worked hard on their concurrency issues and now can support fairly large user or reporting loads. They also can handle reasonable volumes of transactional or trickle-feed updates, and probably can support full EDW requirements for decent-sized organizations. Even so, there are some warehouse use cases for which they’re ill-suited. Newer appliance vendors are more limited yet.
- Analytic appliances are just renamed data warehouse appliances. Fact, even if misleading. Netezza is using the term “analytic appliance” to highlight additional things one can do on its boxes beyond answering queries. But those are still operations on a data mart or data warehouse.
- Teradata is the leading data warehouse appliance vendor. More fact than fiction. Some observers say that Teradata systems aren’t data warehouse appliances. But I think they are. Competitors may be superior to Teradata in one or the other characteristic trait of appliances – e.g., speed of installation – but it’s hard to define “appliances” in an objective way that excludes Teradata.
If you liked this post, you might also like one on text mining fact and fiction.
Categories: Analytic technologies, Data warehouse appliances, Data warehousing
Subscribe to our complete feed!