GIS and geospatial

Analysis of data management technology optimized for geospatial data, whether by specialized indexing or user-defined functions

April 17, 2014

MongoDB is growing up

I caught up with my clients at MongoDB to discuss the recent MongoDB 2.6, along with some new statements of direction. The biggest takeaway is that the MongoDB product, along with the associated MMS (MongoDB Management Service), is growing up. Aspects include:

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September 3, 2013

The Hemisphere program

Another surveillance slide deck has emerged, as reported by the New York Times and other media outlets. This one is for the Hemisphere program, which apparently:

Other notes include:

I’ve never gotten a single consistent figure, but typical CDR size seems to be in the 100s of bytes range. So I conjecture that Project Hemisphere spawned one of the first petabyte-scale databases ever.

Hemisphere Project unknowns start:  Read more

August 24, 2013

Hortonworks business notes

Hortonworks did a business-oriented round of outreach, talking with at least Derrick Harris and me. Notes  from my call — for which Rob Bearden* didn’t bother showing up — include, in no particular order:

*Speaking of CEO Bearden, an interesting note from Derrick’s piece is that Bearden is quoted as saying “I started this company from day one …”, notwithstanding that the now-departed Eric Baldeschwieler was founding CEO.

In Hortonworks’ view, Hadoop adopters typically start with a specific use case around a new type of data, such as clickstream, sensor, server log, geolocation, or social.  Read more

April 25, 2013

Analytic application themes

I talk with a lot of companies, and repeatedly hear some of the same application themes. This post is my attempt to collect some of those ideas in one place.

1. So far, the buzzword of the year is “real-time analytics”, generally with “operational” or “big data” included as well. I hear variants of that positioning from NewSQL vendors (e.g. MemSQL), NoSQL vendors (e.g. AeroSpike), BI stack vendors (e.g. Platfora), application-stack vendors (e.g. WibiData), log analysis vendors (led by Splunk), data management vendors (e.g. Cloudera), and of course the CEP industry.

Yeah, yeah, I know — not all the named companies are in exactly the right market category. But that’s hard to avoid.

Why this gold rush? On the demand side, there’s a real or imagined need for speed. On the supply side, I’d say:

2. More generally, most of the applications I hear about are analytic, or have a strong analytic aspect. The three biggest areas — and these overlap — are:

Also arising fairly frequently are:

I’m hearing less about quality, defect tracking, and equipment maintenance than I used to, but those application areas have anyway been ebbing and flowing for decades.

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February 21, 2013

One database to rule them all?

Perhaps the single toughest question in all database technology is: Which different purposes can a single data store serve well? — or to phrase it more technically — Which different usage patterns can a single data store support efficiently? Ted Codd was on multiple sides of that issue, first suggesting that relational DBMS could do everything and then averring they could not. Mike Stonebraker too has been on multiple sides, first introducing universal DBMS attempts with Postgres and Illustra/Informix, then more recently suggesting the world needs 9 or so kinds of database technology. As for me — well, I agreed with Mike both times. :)

Since this is MUCH too big a subject for a single blog post, what I’ll do in this one is simply race through some background material. To a first approximation, this whole discussion is mainly about data layouts — but only if we interpret that concept broadly enough to comprise:

To date, nobody has ever discovered a data layout that is efficient for all usage patterns. As a general rule, simpler data layouts are often faster to write, while fancier ones can boost query performance. Specific tradeoffs include, but hardly are limited to: Read more

July 15, 2012

Memory-centric data management when locality matters

Ron Pressler of Parallel Universe/SpaceBase pinged me about a data grid product he was open sourcing, called Galaxy. The idea is that a distributed RAM grid will allocate data, not randomly or via consistent hashing, but rather via a locality-sensitive approach. Notes include:

The whole thing is discussed in considerable detail in a blog post and a especially in a Hacker News comment thread. There’s also an error-riddled TechCrunch article. Read more

June 20, 2011

Vertica as an analytic platform

Vertica 5.0 is coming out today, and delivering the down payment on Vertica’s analytic platform strategy. In Vertica lingo, there’s now a Vertica SDK (Software Development Kit), featuring Vertica UDT(F)s* (User-Defined Transform Functions). Vertica UDT syntax basics start:  Read more

June 19, 2011

Investigative analytics and derived data: Enzee Universe 2011 talk

I’ll be speaking Monday, June 20 at IBM Netezza’s Enzee Universe conference. Thus, as is my custom:

The talk concept started out as “advanced analytics” (as opposed to fast query, a subject amply covered in the rest of any Netezza event), as a lunch break in what is otherwise a detailed “best practices” session. So I suggested we constrain the subject by focusing on a specific application area — customer acquisition and retention, something of importance to almost any enterprise, and which exploits most areas of analytic technology. Then I actually prepared the slides — and guess what? The mix of subjects will be skewed somewhat more toward generalities than I first intended, specifically in the areas of investigative analytics and derived data. And, as always when I speak, I’ll try to raise consciousness about the issues of liberty and privacy, our options as a society for addressing them, and the crucial role we play as an industry in helping policymakers deal with these technologically-intense subjects.

Slide 3 refers back to a post I made last December, saying there are six useful things you can do with analytic technology:

Slide 4 observes that investigative analytics:

Slide 5 gives my simplest overview of investigative analytics technology to date:  Read more

April 17, 2011

Netezza TwinFin i-Class overview

I have long complained about difficulties in discussing Netezza’s TwinFin i-Class analytic platform. But I’m ready now, and in the grand sweep of the product’s history I’m not even all that late. The Netezza i-Class timing story goes something like this:

My advice to Netezza as to how it should describe TwinFin i-Class boils down to:  Read more

January 20, 2011

Notes, links, and comments January 20, 2011

I haven’t done a pure notes/links/comments post for a while. Let’s fix that now. (A bunch of saved-up links, however, did find their way into my recent privacy threats overview.)

First and foremost, the fourth annual New England Database Summit (nee “Day”) is next week, specifically Friday, January 28. As per my posts in previous years, I think well of the event, which has a friendly, gathering-of-the-clan flavor. Registration is free, but the organizers would prefer that you register online by the end of this week, if you would be so kind.

The two things potentially wrong with the New England Database Summit are parking and the rush hour drive home afterwards. I would listen with interest to any suggestions about dinner plans.

One thing I hope to figure out at the Summit or before is what the hell is going on on Vertica’s blog or, for that matter, at Vertica. The recent Mike Stonebraker post that spawned a lot of discussion and commentary has disappeared. Meanwhile, Vertica has had three consecutive heads of marketing leave the company since June, and I don’t know who to talk to there any more.  Read more

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