Infobright update
Infobright briefed me, and I thought it would be best to invite them to provide a write-up themselves of what customer and other information they did and didn’t want to disclose, for me to publish. Read more
| Categories: Application areas, Data warehousing, Infobright, Open source, Telecommunications, Web analytics | 2 Comments |
IBM in the cloud
IBM is making DB2, Informix Dynamic Server, and other products available in the Amazon cloud. The press release says test and development are free, while production will be charged at an hourly rate. No doubt more price details will be forthcoming when the whole thing is fully in production.
Frankly, I’ve lost track of who all has some kind of cloud or SaaS offering now. The list is at least Oracle, IBM, presumably Microsoft, MySQL (via Elastra, and also at almost every web host), PostgreSQL (ditto, more or less), EnterpriseDB, Kognitio, Vertica, Netezza, Aster Data. No doubt I’m forgetting a bunch more.
| Categories: Cloud computing, Data warehousing, IBM and DB2, Pricing | 2 Comments |
An example of Aster Data’s nPath/MapReduce syntax
Perhaps in response to my prior post on Aster Data’s introduction of MapReduce-based nPath, Steve Wooledge of Aster offers a more detailed example. The particular case he works through is:
… the question: for SEO/SEM-driven traffic that stay on our site only for 5 or less pageviews and then leave our site and never return in the same session, what are the top referring search queries and what are the top path of navigated pages on our site?
| Categories: Analytic technologies, Aster Data, Data warehousing, MapReduce, Web analytics | Leave a Comment |
Aster Data nPath
Edit: Unfortunately, this post and its sequel rely on Aster Data posts that Aster’s buyer Teradata no longer makes easily available.
At the same time as it rolled out its cloud story, Aster Data told of nPath, a MapReduce-based feature in nCluster. As best I understand it, the core idea of nPath is that it preprocesses sequential data via MapReduce so that you can then do ordinary SQL on it. (Steve Wooledge’s blog post about nPath outlines why that might be needed. Point 1 in Mayank Bawa’s August, 2008 post is much more concise. 😉 ) Now, that might seem to contradict the syntax, which is all about MapReduce being invoked via SQL — still, it’s what’s really going on.
That leads to two obvious questions: What is nPath used (or useful) for? and How is the preprocessing done anyway? Read more
| Categories: Aster Data, Data warehousing, MapReduce, Predictive modeling and advanced analytics, Web analytics | 2 Comments |
Aster Data in the cloud
Aster Data is in the news, bragging about a cloud version of nCluster, and providing both a press release and a blog post on the subject. It seems there are three actual customers, two of which have been publicly named. One of them, ShareThis, is in production. (2 terabytes of data on 9 nodes, planning to scale to 10-18 TB on 24 or so nodes by year-end.) All seem to be doing something in the area of internet marketing, web analytics or otherwise — which makes sense, as the same could be said of almost all Aster customers overall. That said, it seems that these customers are doing their primary analytic processing remotely, which makes Aster’s experience in that regard more akin to Kognitio’s than to Vertica’s. Read more
| Categories: Analytic technologies, Application areas, Aster Data, Cloud computing, Data warehousing, MapReduce, Software as a Service (SaaS), Web analytics | 1 Comment |
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
| Categories: Analytic technologies, Application areas, Business intelligence, Cognos, Data warehousing, IBM and DB2, MOLAP | Leave a Comment |
Draft slides on how to select an analytic DBMS
I need to finalize an already-too-long slide deck on how to select an analytic DBMS by late Thursday night. Anybody see something I’m overlooking, or just plain got wrong?
Edit: The slides have now been finalized.
Winter Corporation on Exadata
The most ridiculous analyst study I can recall — at least since Aberdeen pulled back from the “You pay; we say” business — is Winter Corporation’s list of large data warehouses. (Failings include that it only lists warehouses run by software from certain vendors; it doesn’t even list most of the largest warehouses from those vendors; and its size metrics are in my opinion fried.) So it was with some trepidation that I approached what appears to be an Oracle-sponsored Winter Corporation white paper about Exadata.* Read more
| Categories: Data warehouse appliances, Data warehousing, Exadata, Oracle | 5 Comments |
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
| Categories: Analytic technologies, Data warehousing, EMC, MOLAP, Solid-state memory, Storage | 2 Comments |
Oracle Exadata article — up at last
I’d been promising Intelligent Enterprise editor Doug Henschen an article on Oracle Exadata for months. It’s finally up. For a variety of reasons, it was a lot more work than one might at first guess. One such reason is that it spawned four related blog posts over the past few days.
As I post this, there are two glitches in the article. One is that em dashes are appearing as quote marks — and as you know, I use a lot of em dashes. The other is that one sentence on in-database data mining seems unclear to me, and I’ve asked for a small edit to make it clearer what I’m talking about. No doubt both will be cleared up soon. Edit: Doug indeed fixed all that within minutes.
This is an edited article. Other than columns, it may be my first such since the Upside Magazine cover story on AOL over a decade ago. But it was edited with a light and skillful touch. Please don’t hold me responsible for every minor subtlety of emphasis or grammatical nuance. But otherwise I stand behind the opinions, for they are indeed mine.
| Categories: About this blog, Data warehouse appliances, Exadata, Oracle | 1 Comment |